1
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Gentili PL, Stano P. Living cells and biological mechanisms as prototypes for developing chemical artificial intelligence. Biochem Biophys Res Commun 2024; 720:150060. [PMID: 38754164 DOI: 10.1016/j.bbrc.2024.150060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 03/25/2024] [Accepted: 05/06/2024] [Indexed: 05/18/2024]
Abstract
Artificial Intelligence (AI) is having a revolutionary impact on our societies. It is helping humans in facing the global challenges of this century. Traditionally, AI is developed in software or through neuromorphic engineering in hardware. More recently, a brand-new strategy has been proposed. It is the so-called Chemical AI (CAI), which exploits molecular, supramolecular, and systems chemistry in wetware to mimic human intelligence. In this work, two promising approaches for boosting CAI are described. One regards designing and implementing neural surrogates that can communicate through optical or chemical signals and give rise to networks for computational purposes and to develop micro/nanorobotics. The other approach concerns "bottom-up synthetic cells" that can be exploited for applications in various scenarios, including future nano-medicine. Both topics are presented at a basic level, mainly to inform the broader audience of non-specialists, and so favour the rise of interest in these frontier subjects.
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Affiliation(s)
- Pier Luigi Gentili
- Department of Chemistry, Biology, and Biotechnology, Università degli Studi di Perugia, Perugia, Italy.
| | - Pasquale Stano
- Department of Biological and Environmental Sciences and Technologies (DiSTeBA), University of Salento, Lecce, Italy.
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2
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Perez Velazquez JL, Mateos DM, Guevara R, Wennberg R. Unifying biophysical consciousness theories with MaxCon: maximizing configurations of brain connectivity. Front Syst Neurosci 2024; 18:1426986. [PMID: 39135560 PMCID: PMC11317472 DOI: 10.3389/fnsys.2024.1426986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Accepted: 07/09/2024] [Indexed: 08/15/2024] Open
Abstract
There is such a vast proliferation of scientific theories of consciousness that it is worrying some scholars. There are even competitions to test different theories, and the results are inconclusive. Consciousness research, far from converging toward a unifying framework, is becoming more discordant than ever, especially with respect to theoretical elements that do not have a clear neurobiological basis. Rather than dueling theories, an integration across theories is needed to facilitate a comprehensive view on consciousness and on how normal nervous system dynamics can develop into pathological states. In dealing with what is considered an extremely complex matter, we try to adopt a perspective from which the subject appears in relative simplicity. Grounded in experimental and theoretical observations, we advance an encompassing biophysical theory, MaxCon, which incorporates aspects of several of the main existing neuroscientific consciousness theories, finding convergence points in an attempt to simplify and to understand how cellular collective activity is organized to fulfill the dynamic requirements of the diverse theories our proposal comprises. Moreover, a computable index indicating consciousness level is presented. Derived from the level of description of the interactions among cell networks, our proposal highlights the association of consciousness with maximization of the number of configurations of neural network connections -constrained by neuroanatomy, biophysics and the environment- that is common to all consciousness theories.
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Affiliation(s)
- Jose Luis Perez Velazquez
- The Ronin Institute, Montclair, NJ, United States
- Institute for Globally Distributed Open Research and Education, Gothenburg, Sweden
| | - Diego Martin Mateos
- Institute for Globally Distributed Open Research and Education, Gothenburg, Sweden
- Achucarro Basque Centre for Neuroscience, Leioa, Spain
| | - Ramon Guevara
- Department of Physics and Astronomy, Department of Developmental Psychology and Socialization, University of Padua, Padova, Italy
| | - Richard Wennberg
- University Health Network, University of Toronto, Toronto, ON, Canada
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3
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Scharf C, Witkowski O. Rebuilding the Habitable Zone from the Bottom up with Computational Zones. ASTROBIOLOGY 2024; 24:613-627. [PMID: 38853680 DOI: 10.1089/ast.2023.0035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Computation, if treated as a set of physical processes that act on information represented by states of matter, encompasses biological systems, digital systems, and other constructs and may be a fundamental measure of living systems. The opportunity for biological computation, represented in the propagation and selection-driven evolution of information-carrying organic molecular structures, has been partially characterized in terms of planetary habitable zones (HZs) based on primary conditions such as temperature and the presence of liquid water. A generalization of this concept to computational zones (CZs) is proposed, with constraints set by three principal characteristics: capacity (including computation rates), energy, and instantiation (or substrate, including spatial extent). CZs naturally combine traditional habitability factors, including those associated with biological function that incorporate the chemical milieu, constraints on nutrients and free energy, as well as element availability. Two example applications are presented by examining the fundamental thermodynamic work efficiency and Landauer limit of photon-driven biological computation on planetary surfaces and of generalized computation in stellar energy capture structures (a.k.a. Dyson structures). It is suggested that CZs that involve nested structures or substellar objects could manifest unique observational signatures as cool far-infrared emitters. While these latter scenarios are entirely hypothetical, they offer a useful, complementary introduction to the potential universality of CZs.
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Affiliation(s)
- Caleb Scharf
- NASA Ames Research Center, Moffett Field, California, USA
| | - Olaf Witkowski
- Cross Labs, Cross Compass Ltd., Kyoto, Japan
- College of Arts and Sciences, University of Tokyo, Tokyo, Japan
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4
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Levin M. Self-Improvising Memory: A Perspective on Memories as Agential, Dynamically Reinterpreting Cognitive Glue. ENTROPY (BASEL, SWITZERLAND) 2024; 26:481. [PMID: 38920491 PMCID: PMC11203334 DOI: 10.3390/e26060481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 05/20/2024] [Accepted: 05/22/2024] [Indexed: 06/27/2024]
Abstract
Many studies on memory emphasize the material substrate and mechanisms by which data can be stored and reliably read out. Here, I focus on complementary aspects: the need for agents to dynamically reinterpret and modify memories to suit their ever-changing selves and environment. Using examples from developmental biology, evolution, and synthetic bioengineering, in addition to neuroscience, I propose that a perspective on memory as preserving salience, not fidelity, is applicable to many phenomena on scales from cells to societies. Continuous commitment to creative, adaptive confabulation, from the molecular to the behavioral levels, is the answer to the persistence paradox as it applies to individuals and whole lineages. I also speculate that a substrate-independent, processual view of life and mind suggests that memories, as patterns in the excitable medium of cognitive systems, could be seen as active agents in the sense-making process. I explore a view of life as a diverse set of embodied perspectives-nested agents who interpret each other's and their own past messages and actions as best as they can (polycomputation). This synthesis suggests unifying symmetries across scales and disciplines, which is of relevance to research programs in Diverse Intelligence and the engineering of novel embodied minds.
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Affiliation(s)
- Michael Levin
- Department of Biology, Allen Discovery Center, Tufts University, 200 Boston Avenue, Suite 4600, Medford, MA 02155-4243, USA
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5
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Xin G, Fan P, Letaief KB. Semantic Communication: A Survey of Its Theoretical Development. ENTROPY (BASEL, SWITZERLAND) 2024; 26:102. [PMID: 38392357 PMCID: PMC10888479 DOI: 10.3390/e26020102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/20/2024] [Accepted: 01/22/2024] [Indexed: 02/24/2024]
Abstract
In recent years, semantic communication has received significant attention from both academia and industry, driven by the growing demands for ultra-low latency and high-throughput capabilities in emerging intelligent services. Nonetheless, a comprehensive and effective theoretical framework for semantic communication has yet to be established. In particular, finding the fundamental limits of semantic communication, exploring the capabilities of semantic-aware networks, or utilizing theoretical guidance for deep learning in semantic communication are very important yet still unresolved issues. In general, the mathematical theory of semantic communication and the mathematical representation of semantics are referred to as semantic information theory. In this paper, we introduce the pertinent advancements in semantic information theory. Grounded in the foundational work of Claude Shannon, we present the latest developments in semantic entropy, semantic rate-distortion, and semantic channel capacity. Additionally, we analyze some open problems in semantic information measurement and semantic coding, providing a theoretical basis for the design of a semantic communication system. Furthermore, we carefully review several mathematical theories and tools and evaluate their applicability in the context of semantic communication. Finally, we shed light on the challenges encountered in both semantic communication and semantic information theory.
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Affiliation(s)
- Gangtao Xin
- Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China
| | - Pingyi Fan
- Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China
| | - Khaled B Letaief
- Department of Electrical and Computer Engineering, Hong Kong University of Science and Technology (HKUST), Hong Kong 999077
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6
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Lingam M. Information Transmission via Molecular Communication in Astrobiological Environments. ASTROBIOLOGY 2024; 24:84-99. [PMID: 38109216 DOI: 10.1089/ast.2023.0069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
The ubiquity of information transmission via molecular communication between cells is comprehensively documented on Earth; this phenomenon might even have played a vital role in the origin(s) and early evolution of life. Motivated by these considerations, a simple model for molecular communication entailing the diffusion of signaling molecules from transmitter to receiver is elucidated. The channel capacity C (maximal rate of information transmission) and an optimistic heuristic estimate of the actual information transmission rate ℐ are derived for this communication system; the two quantities, especially the latter, are demonstrated to be broadly consistent with laboratory experiments and more sophisticated theoretical models. The channel capacity exhibits a potentially weak dependence on environmental parameters, whereas the actual information transmission rate may scale with the intercellular distance d as ℐ ∝ d-4 and could vary substantially across settings. These two variables are roughly calculated for diverse astrobiological environments, ranging from Earth's upper oceans (C ∼ 3.1 × 103 bits/s; ℐ ∼ 4.7 × 10-2 bits/s) and deep sea hydrothermal vents (C ∼ 4.2 × 103 bits/s; ℐ ∼ 1.2 × 10-1 bits/s) to the hydrocarbon lakes and seas of Titan (C ∼ 3.8 × 103 bits/s; ℐ ∼ 2.6 × 10-1 bits/s).
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Affiliation(s)
- Manasvi Lingam
- Department of Aerospace, Physics and Space Sciences, Florida Institute of Technology, Melbourne, Florida, USA
- Department of Physics, The University of Texas at Austin, Austin, Texas, USA
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7
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O'Sullivan FM, Ryan TJ. If Engrams Are the Answer, What Is the Question? ADVANCES IN NEUROBIOLOGY 2024; 38:273-302. [PMID: 39008021 DOI: 10.1007/978-3-031-62983-9_15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Engram labelling and manipulation methodologies are now a staple of contemporary neuroscientific practice, giving the impression that the physical basis of engrams has been discovered. Despite enormous progress, engrams have not been clearly identified, and it is unclear what they should look like. There is an epistemic bias in engram neuroscience toward characterizing biological changes while neglecting the development of theory. However, the tools of engram biology are exciting precisely because they are not just an incremental step forward in understanding the mechanisms of plasticity and learning but because they can be leveraged to inform theory on one of the fundamental mysteries in neuroscience-how and in what format the brain stores information. We do not propose such a theory here, as we first require an appreciation for what is lacking. We outline a selection of issues in four sections from theoretical biology and philosophy that engram biology and systems neuroscience generally should engage with in order to construct useful future theoretical frameworks. Specifically, what is it that engrams are supposed to explain? How do the different building blocks of the brain-wide engram come together? What exactly are these component parts? And what information do they carry, if they carry anything at all? Asking these questions is not purely the privilege of philosophy but a key to informing scientific hypotheses that make the most of the experimental tools at our disposal. The risk for not engaging with these issues is high. Without a theory of what engrams are, what they do, and the wider computational processes they fit into, we may never know when they have been found.
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Affiliation(s)
- Fionn M O'Sullivan
- School of Biochemistry and Immunology, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Tomás J Ryan
- School of Biochemistry and Immunology, Trinity College Dublin, Dublin, Ireland.
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.
- Florey Institute of Neuroscience and Mental Health, Melbourne Brain Centre, University of Melbourne, Melbourne, VIC, Australia.
- Child & Brain Development Program, Canadian Institute for Advanced Research (CIFAR), Toronto, ON, Canada.
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8
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Safron A, Hipólito I, Clark A. Editorial: Bio A.I. - from embodied cognition to enactive robotics. Front Neurorobot 2023; 17:1301993. [PMID: 38034837 PMCID: PMC10682788 DOI: 10.3389/fnbot.2023.1301993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 10/03/2023] [Indexed: 12/02/2023] Open
Affiliation(s)
- Adam Safron
- Center for Psychedelic and Consciousness Research, Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Institute for Advanced Consciousness Studies, Santa Monica, CA, United States
- Cognitive Science Program, Indiana University, Bloomington, IN, United States
- Kinsey Institute, Indiana University, Bloomington, IN, United States
| | - Inês Hipólito
- Department of Philosophy, Macquarie University, Sydney, NSW, Australia
| | - Andy Clark
- Department of Philosophy, Macquarie University, Sydney, NSW, Australia
- Department of Philosophy and Department of Informatics, University of Sussex, Brighton, United Kingdom
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Baltieri M, Iizuka H, Witkowski O, Sinapayen L, Suzuki K. Hybrid Life: Integrating biological, artificial, and cognitive systems. WILEY INTERDISCIPLINARY REVIEWS. COGNITIVE SCIENCE 2023; 14:e1662. [PMID: 37403661 DOI: 10.1002/wcs.1662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 05/22/2023] [Accepted: 05/30/2023] [Indexed: 07/06/2023]
Abstract
Artificial life is a research field studying what processes and properties define life, based on a multidisciplinary approach spanning the physical, natural, and computational sciences. Artificial life aims to foster a comprehensive study of life beyond "life as we know it" and toward "life as it could be," with theoretical, synthetic, and empirical models of the fundamental properties of living systems. While still a relatively young field, artificial life has flourished as an environment for researchers with different backgrounds, welcoming ideas, and contributions from a wide range of subjects. Hybrid Life brings our attention to some of the most recent developments within the artificial life community, rooted in more traditional artificial life studies but looking at new challenges emerging from interactions with other fields. Hybrid Life aims to cover studies that can lead to an understanding, from first principles, of what systems are and how biological and artificial systems can interact and integrate to form new kinds of hybrid (living) systems, individuals, and societies. To do so, it focuses on three complementary perspectives: theories of systems and agents, hybrid augmentation, and hybrid interaction. Theories of systems and agents are used to define systems, how they differ (e.g., biological or artificial, autonomous, or nonautonomous), and how multiple systems relate in order to form new hybrid systems. Hybrid augmentation focuses on implementations of systems so tightly connected that they act as a single, integrated one. Hybrid interaction is centered around interactions within a heterogeneous group of distinct living and nonliving systems. After discussing some of the major sources of inspiration for these themes, we will focus on an overview of the works that appeared in Hybrid Life special sessions, hosted by the annual Artificial Life Conference between 2018 and 2022. This article is categorized under: Neuroscience > Cognition Philosophy > Artificial Intelligence Computer Science and Robotics > Robotics.
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Affiliation(s)
- Manuel Baltieri
- Araya Inc., Tokyo, Japan
- Department of Informatics, University of Sussex, Brighton, UK
| | - Hiroyuki Iizuka
- Faculty of Information Science and Technology, Hokkaido University, Sapporo, Japan
- Center for Human Nature, Artificial Intelligence and Neuroscience (CHAIN), Hokkaido University, Sapporo, Japan
| | - Olaf Witkowski
- Center for Human Nature, Artificial Intelligence and Neuroscience (CHAIN), Hokkaido University, Sapporo, Japan
- Cross Labs, Cross Compass, Kyoto, Japan
- College of Arts and Sciences, University of Tokyo, Tokyo, Japan
| | - Lana Sinapayen
- Sony Computer Science Laboratories, Kyoto, Japan
- National Institute for Basic Biology, Okazaki, Japan
| | - Keisuke Suzuki
- Center for Human Nature, Artificial Intelligence and Neuroscience (CHAIN), Hokkaido University, Sapporo, Japan
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10
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Naidoo M. What does it mean to be an agent? Front Psychol 2023; 14:1273470. [PMID: 37915525 PMCID: PMC10616898 DOI: 10.3389/fpsyg.2023.1273470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 09/26/2023] [Indexed: 11/03/2023] Open
Abstract
Artificial intelligence (AI) has posed numerous legal-ethical challenges. These challenges are particularly acute when dealing with AI demonstrating substantial computational prowess, which is then correlated with agency or autonomy. A common response to considering this issue is to inquire whether an AI system is "conscious" or not. If it is, then it could constitute an agent, actor, or person. This framing is, however, unhelpful since there are many unresolved questions about consciousness. Instead, a practical approach is proposed, which could be used to better regulate new AI technologies. The value of the practical approach in this study is that it (1) provides an empirically observable, testable framework that contains predictive value; (2) is derived from a data-science framework that uses semantic information as a marker; (3) relies on a self-referential logic which is fundamental to agency; (4) enables the "grading" or "ranking" of AI systems, which provides an alternative method (as opposed to current risk-tiering approaches) and measure to determine the suitability of an AI system within a specific domain (e.g., such as social domains or emotional domains); (5) presents consistent, coherent, and higher informational content as opposed to other approaches; (6) fits within the conception of what informational content "laws" are to contain and maintain; and (7) presents a viable methodology to obtain "agency", "agent", and "personhood", which is robust to current and future developments in AI technologies and society.
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Stano P. Chemical Systems for Wetware Artificial Life: Selected Perspectives in Synthetic Cell Research. Int J Mol Sci 2023; 24:14138. [PMID: 37762444 PMCID: PMC10532297 DOI: 10.3390/ijms241814138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 09/07/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023] Open
Abstract
The recent and important advances in bottom-up synthetic biology (SB), in particular in the field of the so-called "synthetic cells" (SCs) (or "artificial cells", or "protocells"), lead us to consider the role of wetware technologies in the "Sciences of Artificial", where they constitute the third pillar, alongside the more well-known pillars hardware (robotics) and software (Artificial Intelligence, AI). In this article, it will be highlighted how wetware approaches can help to model life and cognition from a unique perspective, complementary to robotics and AI. It is suggested that, through SB, it is possible to explore novel forms of bio-inspired technologies and systems, in particular chemical AI. Furthermore, attention is paid to the concept of semantic information and its quantification, following the strategy recently introduced by Kolchinsky and Wolpert. Semantic information, in turn, is linked to the processes of generation of "meaning", interpreted here through the lens of autonomy and cognition in artificial systems, emphasizing its role in chemical ones.
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Affiliation(s)
- Pasquale Stano
- Department of Biological and Environmental Sciences and Technologies (DiSTeBA), University of Salento, 73100 Lecce, Italy
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12
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Lingam M, Frank A, Balbi A. Planetary Scale Information Transmission in the Biosphere and Technosphere: Limits and Evolution. Life (Basel) 2023; 13:1850. [PMID: 37763254 PMCID: PMC10532900 DOI: 10.3390/life13091850] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/24/2023] [Accepted: 08/29/2023] [Indexed: 09/29/2023] Open
Abstract
Information transmission via communication between agents is ubiquitous on Earth, and is a vital facet of living systems. In this paper, we aim to quantify this rate of information transmission associated with Earth's biosphere and technosphere (i.e., a measure of global information flow) by means of a heuristic order-of-magnitude model. By adopting ostensibly conservative values for the salient parameters, we estimate that the global information transmission rate for the biosphere might be ∼1024 bits/s, and that it may perhaps exceed the corresponding rate for the current technosphere by ∼9 orders of magnitude. However, under the equivocal assumption of sustained exponential growth, we find that information transmission in the technosphere can potentially surpass that of the biosphere ∼90 years in the future, reflecting its increasing dominance.
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Affiliation(s)
- Manasvi Lingam
- Department of Aerospace, Physics and Space Sciences, Florida Institute of Technology, Melbourne, FL 32901, USA
- Department of Physics and Institute for Fusion Studies, The University of Texas at Austin, Austin, TX 78712, USA
| | - Adam Frank
- Department of Physics and Astronomy, University of Rochester, Rochester, NY 14620, USA
| | - Amedeo Balbi
- Dipartimento di Fisica, Università di Roma “Tor Vergata”, 00133 Roma, Italy
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Stano P, Gentili PL, Damiano L, Magarini M. A Role for Bottom-Up Synthetic Cells in the Internet of Bio-Nano Things? Molecules 2023; 28:5564. [PMID: 37513436 PMCID: PMC10385758 DOI: 10.3390/molecules28145564] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Revised: 06/29/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
The potential role of bottom-up Synthetic Cells (SCs) in the Internet of Bio-Nano Things (IoBNT) is discussed. In particular, this perspective paper focuses on the growing interest in networks of biological and/or artificial objects at the micro- and nanoscale (cells and subcellular parts, microelectrodes, microvessels, etc.), whereby communication takes place in an unconventional manner, i.e., via chemical signaling. The resulting "molecular communication" (MC) scenario paves the way to the development of innovative technologies that have the potential to impact biotechnology, nanomedicine, and related fields. The scenario that relies on the interconnection of natural and artificial entities is briefly introduced, highlighting how Synthetic Biology (SB) plays a central role. SB allows the construction of various types of SCs that can be designed, tailored, and programmed according to specific predefined requirements. In particular, "bottom-up" SCs are briefly described by commenting on the principles of their design and fabrication and their features (in particular, the capacity to exchange chemicals with other SCs or with natural biological cells). Although bottom-up SCs still have low complexity and thus basic functionalities, here, we introduce their potential role in the IoBNT. This perspective paper aims to stimulate interest in and discussion on the presented topics. The article also includes commentaries on MC, semantic information, minimal cognition, wetware neuromorphic engineering, and chemical social robotics, with the specific potential they can bring to the IoBNT.
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Affiliation(s)
- Pasquale Stano
- Department of Biological and Environmental Sciences and Technologies (DiSTeBA), University of Salento, 73100 Lecce, Italy
| | - Pier Luigi Gentili
- Dipartimento di Chimica, Biologia e Biotecnologie, Università degli Studi di Perugia, 06123 Perugia, Italy
| | - Luisa Damiano
- Department of Communication, Arts and Media, IULM University, 20143 Milan, Italy
| | - Maurizio Magarini
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
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14
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Braccini M, Collinson E, Roli A, Fellermann H, Stano P. Recurrent neural networks in synthetic cells: a route to autonomous molecular agents? Front Bioeng Biotechnol 2023; 11:1210334. [PMID: 37351468 PMCID: PMC10284608 DOI: 10.3389/fbioe.2023.1210334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 05/29/2023] [Indexed: 06/24/2023] Open
Affiliation(s)
- Michele Braccini
- Department of Computer Science and Engineering, Alma Mater Studiorum Università di Bologna, Campus of Cesena, Cesena, Italy
| | - Ethan Collinson
- Interdisciplinary Computing and Complex Biosystems Research Group, School of Computing, Newcastle University, Newcastle, United Kingdom
| | - Andrea Roli
- Department of Computer Science and Engineering, Alma Mater Studiorum Università di Bologna, Campus of Cesena, Cesena, Italy
- European Centre for Living Technology (ECLT), Venice, Italy
| | - Harold Fellermann
- Interdisciplinary Computing and Complex Biosystems Research Group, School of Computing, Newcastle University, Newcastle, United Kingdom
- European Centre for Living Technology (ECLT), Venice, Italy
| | - Pasquale Stano
- Department of Biological and Environmental Sciences and Technologies (DiSTeBA), University of Salento, Lecce, Italy
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15
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Wong ML, Prabhu A. Cells as the first data scientists. J R Soc Interface 2023; 20:20220810. [PMID: 36751931 PMCID: PMC9905997 DOI: 10.1098/rsif.2022.0810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/17/2023] [Indexed: 02/09/2023] Open
Abstract
The concepts that we generally associate with the field of data science are strikingly descriptive of the way that life, in general, processes information about its environment. The 'information life cycle', which enumerates the stages of information treatment in data science endeavours, also captures the steps of data collection and handling in biological systems. Similarly, the 'data-information-knowledge ecosystem', developed to illuminate the role of informatics in translating raw data into knowledge, can be a framework for understanding how information is constantly being transferred between life and the environment. By placing the principles of data science in a broader biological context, we see the activities of data scientists as the latest development in life's ongoing journey to better understand and predict its environment. Finally, we propose that informatics frameworks can be used to understand the similarities and differences between abiotic complex evolving systems and life.
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Affiliation(s)
- Michael L. Wong
- Earth and Planets Laboratory, Carnegie Institution for Science, Washington, DC 20015, USA
- NHFP Sagan Fellow, NASA Hubble Fellowship Program, Space Telescope Science Institute, Baltimore, MD 21218, USA
| | - Anirudh Prabhu
- Earth and Planets Laboratory, Carnegie Institution for Science, Washington, DC 20015, USA
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16
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Egan M, Kuscu M, Barros MT, Booth M, Llopis-Lorente A, Magarini M, Martins DP, Schäfer M, Stano P. Toward Interdisciplinary Synergies in Molecular Communications: Perspectives from Synthetic Biology, Nanotechnology, Communications Engineering and Philosophy of Science. Life (Basel) 2023; 13:208. [PMID: 36676156 PMCID: PMC9861838 DOI: 10.3390/life13010208] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 12/18/2022] [Accepted: 12/30/2022] [Indexed: 01/12/2023] Open
Abstract
Within many chemical and biological systems, both synthetic and natural, communication via chemical messengers is widely viewed as a key feature. Often known as molecular communication, such communication has been a concern in the fields of synthetic biologists, nanotechnologists, communications engineers, and philosophers of science. However, interactions between these fields are currently limited. Nevertheless, the fact that the same basic phenomenon is studied by all of these fields raises the question of whether there are unexploited interdisciplinary synergies. In this paper, we summarize the perspectives of each field on molecular communications, highlight potential synergies, discuss ongoing challenges to exploit these synergies, and present future perspectives for interdisciplinary efforts in this area.
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Affiliation(s)
- Malcolm Egan
- Univ Lyon, INSA Lyon, INRIA, CITI, 69621 Villeurbanne, France
| | - Murat Kuscu
- Department of Electrical and Electronics Engineering, Koç University, Istanbul 34450, Turkey
| | - Michael Taynnan Barros
- School of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK
| | - Michael Booth
- Department of Chemistry, University College London (UCL), London WC1H 0AJ, UK
| | - Antoni Llopis-Lorente
- Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Universitat Politècnica de València, Camino de Vera, 46022 València, Spain
| | - Maurizio Magarini
- Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, 20133 Milan, Italy
| | - Daniel P. Martins
- Walton Institute for Information and Communication Systems Science, South East Technological University (SETU), X91 P20H Waterford, Ireland
| | - Maximilian Schäfer
- Institute for Digital Communications, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91058 Erlangen, Germany
| | - Pasquale Stano
- Department of Biological and Environmental Sciences and Technologies (DiSTeBA), University of Salento, 73100 Lecce, Italy
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17
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Xin G, Fan P. EXK-SC: A Semantic Communication Model Based on Information Framework Expansion and Knowledge Collision. ENTROPY (BASEL, SWITZERLAND) 2022; 24:1842. [PMID: 36554247 PMCID: PMC9778631 DOI: 10.3390/e24121842] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 12/05/2022] [Accepted: 12/09/2022] [Indexed: 06/17/2023]
Abstract
Semantic communication is not focused on improving the accuracy of transmitted symbols, but is concerned with expressing the expected meaning that the symbol sequence exactly carries. However, the measurement of semantic messages and their corresponding codebook generation are still open issues. Expansion, which integrates simple things into a complex system and even generates intelligence, is truly consistent with the evolution of the human language system. We apply this idea to the semantic communication system, quantifying semantic transmission by symbol sequences and investigating the semantic information system in a similar way as Shannon's method for digital communication systems. This work is the first to discuss semantic expansion and knowledge collision in the semantic information framework. Some important theoretical results are presented, including the relationship between semantic expansion and the transmission information rate. We believe such a semantic information framework may provide a new paradigm for semantic communications, and semantic expansion and knowledge collision will be the cornerstone of semantic information theory.
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Affiliation(s)
- Gangtao Xin
- Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China
| | - Pingyi Fan
- Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China
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18
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Döbereiner HG. On the Nature of Information: How FAIR Digital Objects are Building-up Semantic Space. RESEARCH IDEAS AND OUTCOMES 2022. [DOI: 10.3897/rio.8.e95119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
In this paper, we are concerned about the nature of information and how to gather and compose data with the help of so called FAIR digital objects (FDOs) in order to transform them to knowledge. FDOs are digital surrogates of real objects. The nature of information is intrinsically linked to the kind of questions one is asking. One might not ask a question or get philosophical about it. Answers depend on the data different disciplines gather about their objects of study. In Statistical Physics, classical Shannon entropy measures system order which in equilibrium just equals the heat exchanged with the environment. In cell biology, each protein carries certain functions which create specific information. Cognitive science describes how organisms perceive their environment via functional sensors and control behavior accordingly. Note that one can have function and control without meaning. In contrast, psychology is concerned with the assessment of our perceptions by assigning meaning and ensuing actions. Finally, philosophy builds logical constructs and formulates principles, in effect transforming facts into complex knowledge. All these statements make sense, but there is an even more concise way. Indeed, Luciano Floridi provides a precise and thorough classification of information in his central oeuvre On the Philosophy of Information (Floridi 2013). Especially, he performs a sequential construction to develop the attributes which data need to have in order to count as knowledge. Semantic information is necessarily well-formed, meaningful and truthful. Well-formed data becomes meaningful by action based-semantics of an autonomous-agent solving the symbol grounding problem (Taddeo and Floridi 2005) interacting with the environment. Knowledge is created then by being informed through relevant data accounted for. We notice that the notion of agency is crucial for defining meaning. The apparent gap between Sciences and Humanities (Bawden and Robinson 2020) is created by the very existence of meaning. Further, meaning depends on interactions & connotations which are commensurate with the effective complexity of the environment of a particular agent resulting in an array of possible definitions.
In his classical paper More is different (Anderson 1972) discussed verbatim the hierarchical nature of science. Each level is made of and obeys the laws of its constituents from one level below with the higher-level exhibiting emergent properties like wetness of water assignable only to the whole system. As we rise through the hierarchies, there is a branch of science for each level of complexity; on each complexity level there are objects for which it is appropriate and fitting to build up vocabulary for the respective levels of description leading to formation of disciplinary languages. It is the central idea of causal emergence that on each level there is an optimal degree of coarse graining to define those objects in such a way that causality becomes maximal between them. This means there is emergence of informative higher scales in complex materials extending to biological systems and into the brain with its neural networks representing our thoughts in a hierarchy of neural correlates. A computational toolkit for optimal level prediction and control has been developed (Hoel and Levin 2020) which was conceptually extended to integrated information theory of consciousness (Albantakis et al. 2019). The large gap between sciences and humanities discussed above exhibits itself in a series of small gaps connected to the emergence of informative higher scales. It has been suggested that the origin of life may be identified as a transition in causal structure and information flow (Walker 2014). Integrated information measures globally how much the causal mechanisms of a system reduce the uncertainty about the possible causes for a given state. A measure of “information flow” that accurately captures causal effects has been proposed (Ay and Polani 2008). The state of the art is presented in (Ay et al. 2022) where the link between information and complexity is discussed. Ay et al single out hierarchical systems and interlevel causation. Even further, (Rosas et al. 2020) reconcile conflicting views of emergence via an exact information-theoretic approach to identify causal emergence in multivariate data. As information becomes differentially richer one eventually needs complexity measures beyond {Rn}. One may define generalized metrices on these spaces (Pirró 2009) measuring information complexity on ever higher hierarchical levels of information. As one rises through hierarchies, information on higher scale is usually gained by coarse graining to arrive at an effective, nevertheless exact description, on the higher scale. It is repeated coarse graining of syntactically well-ordered information layers which eventually leads to semantic information in a process which I conjecture to be reminiscent of renormalization group flow leading to a universal classification scheme. Thus, we identify scientific disciplines and their corresponding data sets as dual universality classes of physical and epistemic structure formation, respectively. Above the semantic gap, we may call this process quantification of the qualitative by semantic metrics. Indeed, (Kolchinsky and Wolpert 2018) explored for the first time quantitative semantic concepts in Physics in their 2018 seminal paper entitled Semantic information, autonomous agency and non-equilibrium statistical physics. Their measures are numeric variants of entropy. Semantic information is identified with ‘the information that a physical system has about its environment that is causally necessary for the system to maintain its own existence over time’.
FDOs are employed in these processes in two fundamental ways. For practical implementations of FDO technology, see accompanying abstract (Wittenburg et al. 2022). First, the FAIR principles (Wilkinson et al. 2016) ensure that unconnected pieces of data may be percolated into an integrated data space. Percolation creates the information density needed to feed AI-driven built up of semantic space. Without FDOs we wouldn't have the gravity for this to occur. Second, the very structure of FDOs, capable of symmetry preserving or breaking fusion events into composed entities, makes them homologous to mathematical categories. This will proof to be a powerful tool to unravel the nature of information via analyzing its topological structure algebraically, especially when considering our conjecture concerning universality, classes of information and their possible instantiations on vastly different length and time scales, in effect explaining analogous structure formation.
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Liu Y, Di Z, Gerlee P. Ladderpath Approach: How Tinkering and Reuse Increase Complexity and Information. ENTROPY (BASEL, SWITZERLAND) 2022; 24:1082. [PMID: 36010747 PMCID: PMC9407278 DOI: 10.3390/e24081082] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 07/29/2022] [Accepted: 08/03/2022] [Indexed: 06/15/2023]
Abstract
The notion of information and complexity are important concepts in many scientific fields such as molecular biology, evolutionary theory and exobiology. Many measures of these quantities are either difficult to compute, rely on the statistical notion of information, or can only be applied to strings. Based on assembly theory, we propose the notion of a ladderpath, which describes how an object can be decomposed into hierarchical structures using repetitive elements. From the ladderpath, two measures naturally emerge: the ladderpath-index and the order-index, which represent two axes of complexity. We show how the ladderpath approach can be applied to both strings and spatial patterns and argue that all systems that undergo evolution can be described as ladderpaths. Further, we discuss possible applications to human language and the origin of life. The ladderpath approach provides an alternative characterization of the information that is contained in a single object (or a system) and could aid in our understanding of evolving systems and the origin of life in particular.
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Affiliation(s)
- Yu Liu
- International Academic Center of Complex Systems, Beijing Normal University, Zhuhai 519087, China
| | - Zengru Di
- International Academic Center of Complex Systems, Beijing Normal University, Zhuhai 519087, China
| | - Philip Gerlee
- Department of Mathematical Sciences, Chalmers University of Technology, 405 30 Gothenburg, Sweden
- Department of Mathematical Sciences, University of Gothenburg, 405 30 Gothenburg, Sweden
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20
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Stano P. Exploring Information and Communication Theories for Synthetic Cell Research. Front Bioeng Biotechnol 2022; 10:927156. [PMID: 35910013 PMCID: PMC9334554 DOI: 10.3389/fbioe.2022.927156] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Accepted: 06/24/2022] [Indexed: 01/17/2023] Open
Affiliation(s)
- Pasquale Stano
- Department of Biological and Environmental Sciences and Technologies (DiSTeBA), University of Salento, Lecce, Italy
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21
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Kiverstein J, Kirchhoff MD, Froese T. The Problem of Meaning: The Free Energy Principle and Artificial Agency. Front Neurorobot 2022; 16:844773. [PMID: 35812784 PMCID: PMC9260223 DOI: 10.3389/fnbot.2022.844773] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 05/17/2022] [Indexed: 12/13/2022] Open
Abstract
Biological agents can act in ways that express a sensitivity to context-dependent relevance. So far it has proven difficult to engineer this capacity for context-dependent sensitivity to relevance in artificial agents. We give this problem the label the "problem of meaning". The problem of meaning could be circumvented if artificial intelligence researchers were to design agents based on the assumption of the continuity of life and mind. In this paper, we focus on the proposal made by enactive cognitive scientists to design artificial agents that possess sensorimotor autonomy-stable, self-sustaining patterns of sensorimotor interaction that can ground values, norms and goals necessary for encountering a meaningful environment. More specifically, we consider whether the Free Energy Principle (FEP) can provide formal tools for modeling sensorimotor autonomy. There is currently no consensus on how to understand the relationship between enactive cognitive science and the FEP. However, a number of recent papers have argued that the two frameworks are fundamentally incompatible. Some argue that biological systems exhibit historical path-dependent learning that is absent from systems that minimize free energy. Others have argued that a free energy minimizing system would fail to satisfy a key condition for sensorimotor agency referred to as "interactional asymmetry". These critics question the claim we defend in this paper that the FEP can be used to formally model autonomy and adaptivity. We will argue it is too soon to conclude that the two frameworks are incompatible. There are undeniable conceptual differences between the two frameworks but in our view each has something important and necessary to offer. The FEP needs enactive cognitive science for the solution it provides to the problem of meaning. Enactive cognitive science needs the FEP to formally model the properties it argues to be constitutive of agency. Our conclusion will be that active inference models based on the FEP provides a way by which scientists can think about how to address the problems of engineering autonomy and adaptivity in artificial agents in formal terms. In the end engaging more closely with this formalism and its further developments will benefit those working within the enactive framework.
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Affiliation(s)
- Julian Kiverstein
- Academic Medical Center, Amsterdam, Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Michael D. Kirchhoff
- Faculty of Arts, Social Sciences, and Humanities, School of Liberal Arts, University of Wollongong, Wollongong, NSW, Australia
| | - Tom Froese
- Embodied Cognitive Science Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
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22
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Barker TS, Pierobon M, Thomas PJ. Subjective Information and Survival in a Simulated Biological System. ENTROPY 2022; 24:e24050639. [PMID: 35626524 PMCID: PMC9142001 DOI: 10.3390/e24050639] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 03/25/2022] [Accepted: 04/25/2022] [Indexed: 02/01/2023]
Abstract
Information transmission and storage have gained traction as unifying concepts to characterize biological systems and their chances of survival and evolution at multiple scales. Despite the potential for an information-based mathematical framework to offer new insights into life processes and ways to interact with and control them, the main legacy is that of Shannon’s, where a purely syntactic characterization of information scores systems on the basis of their maximum information efficiency. The latter metrics seem not entirely suitable for biological systems, where transmission and storage of different pieces of information (carrying different semantics) can result in different chances of survival. Based on an abstract mathematical model able to capture the parameters and behaviors of a population of single-celled organisms whose survival is correlated to information retrieval from the environment, this paper explores the aforementioned disconnect between classical information theory and biology. In this paper, we present a model, specified as a computational state machine, which is then utilized in a simulation framework constructed specifically to reveal emergence of a “subjective information”, i.e., trade-off between a living system’s capability to maximize the acquisition of information from the environment, and the maximization of its growth and survival over time. Simulations clearly show that a strategy that maximizes information efficiency results in a lower growth rate with respect to the strategy that gains less information but contains a higher meaning for survival.
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Affiliation(s)
- Tyler S. Barker
- School of Computing, College of Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA;
| | - Massimiliano Pierobon
- School of Computing, College of Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA;
- Correspondence:
| | - Peter J. Thomas
- Department of Mathematics, Applied Mathematics and Statistics, Case Western Reserve University, Cleveland, OH 44106, USA;
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23
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Sims M. Self-Concern Across Scales: A Biologically Inspired Direction for Embodied Artificial Intelligence. Front Neurorobot 2022; 16:857614. [PMID: 35574229 PMCID: PMC9106101 DOI: 10.3389/fnbot.2022.857614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 03/16/2022] [Indexed: 12/02/2022] Open
Abstract
Intelligence in current AI research is measured according to designer-assigned tasks that lack any relevance for an agent itself. As such, tasks and their evaluation reveal a lot more about our intelligence than the possible intelligence of agents that we design and evaluate. As a possible first step in remedying this, this article introduces the notion of “self-concern,” a property of a complex system that describes its tendency to bring about states that are compatible with its continued self-maintenance. Self-concern, as argued, is the foundation of the kind of basic intelligence found across all biological systems, because it reflects any such system's existential task of continued viability. This article aims to cautiously progress a few steps closer to a better understanding of some necessary organisational conditions that are central to self-concern in biological systems. By emulating these conditions in embodied AI, perhaps something like genuine self-concern can be implemented in machines, bringing AI one step closer to its original goal of emulating human-like intelligence.
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24
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Grzywacz NM, Aleem H. Does Amount of Information Support Aesthetic Values? Front Neurosci 2022; 16:805658. [PMID: 35392414 PMCID: PMC8982361 DOI: 10.3389/fnins.2022.805658] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Accepted: 02/16/2022] [Indexed: 11/24/2022] Open
Abstract
Obtaining information from the world is important for survival. The brain, therefore, has special mechanisms to extract as much information as possible from sensory stimuli. Hence, given its importance, the amount of available information may underlie aesthetic values. Such information-based aesthetic values would be significant because they would compete with others to drive decision-making. In this article, we ask, "What is the evidence that amount of information support aesthetic values?" An important concept in the measurement of informational volume is entropy. Research on aesthetic values has thus used Shannon entropy to evaluate the contribution of quantity of information. We review here the concepts of information and aesthetic values, and research on the visual and auditory systems to probe whether the brain uses entropy or other relevant measures, specially, Fisher information, in aesthetic decisions. We conclude that information measures contribute to these decisions in two ways: first, the absolute quantity of information can modulate aesthetic preferences for certain sensory patterns. However, the preference for volume of information is highly individualized, with information-measures competing with organizing principles, such as rhythm and symmetry. In addition, people tend to be resistant to too much entropy, but not necessarily, high amounts of Fisher information. We show that this resistance may stem in part from the distribution of amount of information in natural sensory stimuli. Second, the measurement of entropic-like quantities over time reveal that they can modulate aesthetic decisions by varying degrees of surprise given temporally integrated expectations. We propose that amount of information underpins complex aesthetic values, possibly informing the brain on the allocation of resources or the situational appropriateness of some cognitive models.
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Affiliation(s)
- Norberto M. Grzywacz
- Department of Psychology, Loyola University Chicago, Chicago, IL, United States
- Department of Molecular Pharmacology and Neuroscience, Loyola University Chicago, Chicago, IL, United States
- Interdisciplinary Program in Neuroscience, Georgetown University, Washington, DC, United States
| | - Hassan Aleem
- Interdisciplinary Program in Neuroscience, Georgetown University, Washington, DC, United States
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25
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Richardson K. Genes and knowledge: Response to Baverstock, K. the gene an appraisal. https://doi.org/10.1016/j.pbiomolbio.2021.04.005. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2021; 167:12-17. [PMID: 34736965 DOI: 10.1016/j.pbiomolbio.2021.10.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 09/21/2021] [Accepted: 10/26/2021] [Indexed: 06/13/2023]
Abstract
This response aims to expand on some of the issues raised by Keith Baverstock's The Gene: An Appraisal, especially on the evolution and nature of knowledge in living things. In contrast to the simple associationism envisaged in "genetic information", it emphasises the dynamic complexity and changeability of most natural environments, and, therefore, predictability based on underlying statistical structures. That seems to be the basis of the "cognitive" functions increasingly being reported about cellular, as well as more evolved, functions, and of the autonomous agency of organisms thriving creatively in complex environments.
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26
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Albantakis L. Quantifying the Autonomy of Structurally Diverse Automata: A Comparison of Candidate Measures. ENTROPY (BASEL, SWITZERLAND) 2021; 23:1415. [PMID: 34828113 PMCID: PMC8624265 DOI: 10.3390/e23111415] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/16/2021] [Accepted: 10/26/2021] [Indexed: 11/16/2022]
Abstract
Should the internal structure of a system matter when it comes to autonomy? While there is still no consensus on a rigorous, quantifiable definition of autonomy, multiple candidate measures and related quantities have been proposed across various disciplines, including graph-theory, information-theory, and complex system science. Here, I review and compare a range of measures related to autonomy and intelligent behavior. To that end, I analyzed the structural, information-theoretical, causal, and dynamical properties of simple artificial agents evolved to solve a spatial navigation task, with or without a need for associative memory. By contrast to standard artificial neural networks with fixed architectures and node functions, here, independent evolution simulations produced successful agents with diverse neural architectures and functions. This makes it possible to distinguish quantities that characterize task demands and input-output behavior, from those that capture intrinsic differences between substrates, which may help to determine more stringent requisites for autonomous behavior and the means to measure it.
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Affiliation(s)
- Larissa Albantakis
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI 53719, USA
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27
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Mizraji E. The biological Maxwell's demons: exploring ideas about the information processing in biological systems. Theory Biosci 2021; 140:307-318. [PMID: 34449033 PMCID: PMC8568868 DOI: 10.1007/s12064-021-00354-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 08/09/2021] [Indexed: 11/28/2022]
Abstract
This work is based on ideas supported by some of the biologists who discovered foundational facts of twentieth-century biology and who argued that Maxwell's demons are physically implemented by biological devices. In particular, JBS Haldane first, and later J. Monod, A, Lwoff and F. Jacob argued that enzymes and molecular receptors implemented Maxwell's demons that operate in systems far removed from thermodynamic equilibrium and that were responsible for creating the biological order. Later, these ideas were extended to other biological processes. In this article, we argue that these biological Maxwell's demons (BMD) are systems that have information processing capabilities that allow them to select their inputs and direct their outputs toward targets. In this context, we propose the idea that these BMD are information catalysts in which the processed information has broad thermodynamic consequences.
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Affiliation(s)
- Eduardo Mizraji
- Group of Cognitive Systems Modeling, Biophysics and Systems Biology Section, Facultad de Ciencias, Universidad de la República, Iguá 4225, 11400, Montevideo, Uruguay.
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28
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Information Entropy in Chemistry: An Overview. ENTROPY 2021; 23:e23101240. [PMID: 34681964 PMCID: PMC8534366 DOI: 10.3390/e23101240] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 09/19/2021] [Accepted: 09/20/2021] [Indexed: 12/20/2022]
Abstract
Basic applications of the information entropy concept to chemical objects are reviewed. These applications deal with quantifying chemical and electronic structures of molecules, signal processing, structural studies on crystals, and molecular ensembles. Recent advances in the mentioned areas make information entropy a central concept in interdisciplinary studies on digitalizing chemical reactions, chemico-information synthesis, crystal engineering, as well as digitally rethinking basic notions of structural chemistry in terms of informatics.
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Mindt G. Not All Structure and Dynamics Are Equal. ENTROPY (BASEL, SWITZERLAND) 2021; 23:1226. [PMID: 34573851 PMCID: PMC8470373 DOI: 10.3390/e23091226] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 09/01/2021] [Accepted: 09/13/2021] [Indexed: 12/04/2022]
Abstract
The hard problem of consciousness has been a perennially vexing issue for the study of consciousness, particularly in giving a scientific and naturalized account of phenomenal experience. At the heart of the hard problem is an often-overlooked argument, which is at the core of the hard problem, and that is the structure and dynamics (S&D) argument. In this essay, I will argue that we have good reason to suspect that the S&D argument given by David Chalmers rests on a limited conception of S&D properties, what in this essay I'm calling extrinsic structure and dynamics. I argue that if we take recent insights from the complexity sciences and from recent developments in Integrated Information Theory (IIT) of Consciousness, that we get a more nuanced picture of S&D, specifically, a class of properties I'm calling intrinsic structure and dynamics. This I think opens the door to a broader class of properties with which we might naturally and scientifically explain phenomenal experience, as well as the relationship between syntactic, semantic, and intrinsic notions of information. I argue that Chalmers' characterization of structure and dynamics in his S&D argument paints them with too broad a brush and fails to account for important nuances, especially when considering accounting for a system's intrinsic properties. Ultimately, my hope is to vindicate a certain species of explanation from the S&D argument, and by extension dissolve the hard problem of consciousness at its core, by showing that not all structure and dynamics are equal.
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Affiliation(s)
- Garrett Mindt
- Elizabeth R Koch Research Fellow, Tiny Blue Dot Foundation for Consciousness Studies, Department of Psychiatry, University of Wisconsin-Madison, Madison, WI 53719, USA
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30
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Kempes CP, Krakauer DC. The Multiple Paths to Multiple Life. J Mol Evol 2021; 89:415-426. [PMID: 34254169 PMCID: PMC8318961 DOI: 10.1007/s00239-021-10016-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 06/08/2021] [Indexed: 12/04/2022]
Abstract
We argue for multiple forms of life realized through multiple different historical pathways. From this perspective, there have been multiple origins of life on Earth—life is not a universal homology. By broadening the class of originations, we significantly expand the data set for searching for life. Through a computational analogy, the origin of life describes both the origin of hardware (physical substrate) and software (evolved function). Like all information-processing systems, adaptive systems possess a nested hierarchy of levels, a level of function optimization (e.g., fitness maximization), a level of constraints (e.g., energy requirements), and a level of materials (e.g., DNA or RNA genome and cells). The functions essential to life are realized by different substrates with different efficiencies. The functional level allows us to identify multiple origins of life by searching for key principles of optimization in different material form, including the prebiotic origin of proto-cells, the emergence of culture, economic, and legal institutions, and the reproduction of software agents.
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Smith HH, Hyde AS, Simkus DN, Libby E, Maurer SE, Graham HV, Kempes CP, Sherwood Lollar B, Chou L, Ellington AD, Fricke GM, Girguis PR, Grefenstette NM, Pozarycki CI, House CH, Johnson SS. The Grayness of the Origin of Life. Life (Basel) 2021; 11:498. [PMID: 34072344 PMCID: PMC8226951 DOI: 10.3390/life11060498] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 05/22/2021] [Accepted: 05/26/2021] [Indexed: 12/05/2022] Open
Abstract
In the search for life beyond Earth, distinguishing the living from the non-living is paramount. However, this distinction is often elusive, as the origin of life is likely a stepwise evolutionary process, not a singular event. Regardless of the favored origin of life model, an inherent "grayness" blurs the theorized threshold defining life. Here, we explore the ambiguities between the biotic and the abiotic at the origin of life. The role of grayness extends into later transitions as well. By recognizing the limitations posed by grayness, life detection researchers will be better able to develop methods sensitive to prebiotic chemical systems and life with alternative biochemistries.
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Affiliation(s)
- Hillary H. Smith
- Department of Geosciences, The Pennsylvania State University, University Park, PA 16802, USA;
- Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, PA 16802, USA
| | - Andrew S. Hyde
- Department of Geosciences, The Pennsylvania State University, University Park, PA 16802, USA;
- Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, PA 16802, USA
| | - Danielle N. Simkus
- NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA; (D.N.S.); (H.V.G.); (L.C.); (C.I.P.)
- NASA Postdoctoral Program, USRA, Columbia, MD 20146, USA
- Department of Physics, Catholic University of America, Washington, DC 20064, USA
| | - Eric Libby
- Santa Fe Institute, Santa Fe, NM 87501, USA; (E.L.); (C.P.K.); (N.M.G.)
- Department of Mathematics and Mathematical Statistics, Umeå University, 90187 Umeå, Sweden
- Icelab, Umeå University, 90187 Umeå, Sweden
| | - Sarah E. Maurer
- Department of Chemistry and Biochemistry, Central Connecticut State University, New Britain, CT 06050, USA;
| | - Heather V. Graham
- NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA; (D.N.S.); (H.V.G.); (L.C.); (C.I.P.)
- Department of Physics, Catholic University of America, Washington, DC 20064, USA
| | | | | | - Luoth Chou
- NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA; (D.N.S.); (H.V.G.); (L.C.); (C.I.P.)
- NASA Postdoctoral Program, USRA, Columbia, MD 20146, USA
- Department of Biology, Georgetown University, Washington, DC 20057, USA
| | - Andrew D. Ellington
- Department of Molecular Biosciences, College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA;
- Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, TX 78712, USA
| | - G. Matthew Fricke
- Department of Computer Science, University of New Mexico, Albuquerque, NM 87108, USA;
| | - Peter R. Girguis
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA;
| | - Natalie M. Grefenstette
- Santa Fe Institute, Santa Fe, NM 87501, USA; (E.L.); (C.P.K.); (N.M.G.)
- Blue Marble Space Institute of Science, Seattle, WA 98104, USA
| | - Chad I. Pozarycki
- NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA; (D.N.S.); (H.V.G.); (L.C.); (C.I.P.)
- Department of Biology, Georgetown University, Washington, DC 20057, USA
| | - Christopher H. House
- Department of Geosciences, The Pennsylvania State University, University Park, PA 16802, USA;
- Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, PA 16802, USA
| | - Sarah Stewart Johnson
- Department of Biology, Georgetown University, Washington, DC 20057, USA
- Science, Technology and International Affairs Program, Georgetown University, Washington, DC 20057, USA
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The Natural Philosophy of Economic Information: Autonomous Agents and Physiosemiosis. ENTROPY 2021; 23:e23030277. [PMID: 33669029 PMCID: PMC7996504 DOI: 10.3390/e23030277] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 02/23/2021] [Accepted: 02/23/2021] [Indexed: 11/16/2022]
Abstract
Information is a core concept in modern economics, yet its definition and empirical specification is elusive. One reason is the intellectual grip of the Shannon paradigm which marginalizes semantic information. However, a precise concept of economic information must be based on a theory of semantics, since what counts economically is the meaning, function and use of information. This paper introduces a new principled approach to information that adopts the paradigm of biosemiotics, rooted in the philosophy of Charles S. Peirce and builds on recent developments of the thermodynamics of information. Information processing by autonomous agents, defined as autopoietic heat engines, is conceived as physiosemiosis operating according to fundamental thermodynamic principles of information processing, as elucidated in recent work by Kolchinsky and Wolpert (KW). I plug the KW approach into a basic conceptual model of physiosemiosis and present an evolutionary interpretation. This approach has far-reaching implications for economics, such as suggesting an evolutionary view of the economic agent, choice and behavior, which is informed by applications of statistical thermodynamics on the brain.
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Surov IA, Semenenko E, Platonov AV, Bessmertny IA, Galofaro F, Toffano Z, Khrennikov AY, Alodjants AP. Quantum semantics of text perception. Sci Rep 2021; 11:4193. [PMID: 33603018 PMCID: PMC7893056 DOI: 10.1038/s41598-021-83490-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 01/25/2021] [Indexed: 01/31/2023] Open
Abstract
The paper presents quantum model of subjective text perception based on binary cognitive distinctions corresponding to words of natural language. The result of perception is quantum cognitive state represented by vector in the qubit Hilbert space. Complex-valued structure of the quantum state space extends the standard vector-based approach to semantics, allowing to account for subjective dimension of human perception in which the result is constrained, but not fully predetermined by input information. In the case of two distinctions, the perception model generates a two-qubit state, entanglement of which quantifies semantic connection between the corresponding words. This two-distinction perception case is realized in the algorithm for detection and measurement of semantic connectivity between pairs of words. The algorithm is experimentally tested with positive results. The developed approach to cognitive modeling unifies neurophysiological, linguistic, and psychological descriptions in a mathematical and conceptual structure of quantum theory, extending horizons of machine intelligence.
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Affiliation(s)
| | - E Semenenko
- ITMO University, St. Petersburg, Russia, 197101
| | | | | | - F Galofaro
- Politecnico Milano, Italy Free University of Bozen, 39100, Bozen, Italy
| | - Z Toffano
- Laboratoire des Signaux et Systemes - L2S (UMR8506) - CNRS, Universite Paris-Saclay, Paris, France
| | - A Yu Khrennikov
- International Center for Mathematical Modeling in Physics and Cognitive Sciences, Linnaeus University, 351 95, Växjö, Sweden.
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Roli A, Kauffman SA. Emergence of Organisms. ENTROPY (BASEL, SWITZERLAND) 2020; 22:E1163. [PMID: 33286932 PMCID: PMC7597334 DOI: 10.3390/e22101163] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 10/03/2020] [Accepted: 10/12/2020] [Indexed: 11/16/2022]
Abstract
Since early cybernetics studies by Wiener, Pask, and Ashby, the properties of living systems are subject to deep investigations. The goals of this endeavour are both understanding and building: abstract models and general principles are sought for describing organisms, their dynamics and their ability to produce adaptive behavior. This research has achieved prominent results in fields such as artificial intelligence and artificial life. For example, today we have robots capable of exploring hostile environments with high level of self-sufficiency, planning capabilities and able to learn. Nevertheless, the discrepancy between the emergence and evolution of life and artificial systems is still huge. In this paper, we identify the fundamental elements that characterize the evolution of the biosphere and open-ended evolution, and we illustrate their implications for the evolution of artificial systems. Subsequently, we discuss the most relevant issues and questions that this viewpoint poses both for biological and artificial systems.
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Affiliation(s)
- Andrea Roli
- Department of Computer Science and Engineering, Alma Mater Studiorum Università di Bologna, Campus of Cesena, I-47522 Cesena, Italy
- European Centre for Living Technology, I-30123 Venezia, Italy
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35
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Sabirov D, Koledina K. Classification of isentropic molecules in terms of Shannon entropy. EPJ WEB OF CONFERENCES 2020. [DOI: 10.1051/epjconf/202024401016] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Shannon entropy is widely used as a descriptor of molecular structure. Isentropicity of the molecules in terms of Shannon approach emerges in specific problems of physical and organic chemistry. In the present work, we consider the main classes of isentropic molecules, exemplify them, and provide their hierarchy.
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36
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Falasco G, Esposito M. Dissipation-Time Uncertainty Relation. PHYSICAL REVIEW LETTERS 2020; 125:120604. [PMID: 33016734 DOI: 10.1103/physrevlett.125.120604] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Accepted: 08/14/2020] [Indexed: 05/10/2023]
Abstract
We show that the entropy production rate bounds the rate at which physical processes can be performed in stochastic systems far from equilibrium. In particular, we prove the fundamental tradeoff ⟨S[over ˙]_{e}⟩T≥k_{B} between the entropy flow ⟨S[over ˙]_{e}⟩ into the reservoirs and the mean time T to complete any process whose time-reversed is exponentially rarer. This dissipation-time uncertainty relation is a novel form of speed limit: the smaller the dissipation, the larger the time to perform a process.
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Affiliation(s)
- Gianmaria Falasco
- Complex Systems and Statistical Mechanics, Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg, Luxembourg
| | - Massimiliano Esposito
- Complex Systems and Statistical Mechanics, Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg, Luxembourg
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37
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Abstract
Humanity faces serious social and environmental problems, including climate change and biodiversity loss. Increasingly, scientists, global policy experts, and the general public conclude that incremental approaches to reduce risk are insufficient and transformative change is needed across all sectors of society. However, the meaning of transformation is still unsettled in the literature, as is the proper role of science in fostering it. This paper is the first in a three-part series that adds to the discussion by proposing a novel science-driven research-and-development program aimed at societal transformation. More than a proposal, it offers a perspective and conceptual framework from which societal transformation might be approached. As part of this, it advances a formal mechanics with which to model and understand self-organizing societies of individuals. While acknowledging the necessity of reform to existing societal systems (e.g., governance, economic, and financial systems), the focus of the series is on transformation understood as systems change or systems migration—the de novo development of and migration to new societal systems. The series provides definitions, aims, reasoning, worldview, and a theory of change, and discusses fitness metrics and design principles for new systems. This first paper proposes a worldview, built using ideas from evolutionary biology, complex systems science, cognitive sciences, and information theory, which is intended to serve as the foundation for the R&D program. Subsequent papers in the series build on the worldview to address fitness metrics, system design, and other topics.
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38
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Kiefer AB. Psychophysical identity and free energy. J R Soc Interface 2020; 17:20200370. [PMID: 32752995 PMCID: PMC7482574 DOI: 10.1098/rsif.2020.0370] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 07/09/2020] [Indexed: 11/12/2022] Open
Abstract
An approach to implementing variational Bayesian inference in biological systems is considered, under which the thermodynamic free energy of a system directly encodes its variational free energy. In the case of the brain, this assumption places constraints on the neuronal encoding of generative and recognition densities, in particular requiring a stochastic population code. The resulting relationship between thermodynamic and variational free energies is prefigured in mind-brain identity theses in philosophy and in the Gestalt hypothesis of psychophysical isomorphism.
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Affiliation(s)
- Alex B Kiefer
- Department of Philosophy, Monash University, Clayton, Victoria, Australia
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39
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Jose AM. A framework for parsing heritable information. J R Soc Interface 2020; 17:20200154. [PMID: 32315573 PMCID: PMC7211480 DOI: 10.1098/rsif.2020.0154] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 04/01/2020] [Indexed: 12/21/2022] Open
Abstract
Living systems transmit heritable information using the replicating gene sequences and the cycling regulators assembled around gene sequences. Here, I develop a framework for heredity and development that includes the cycling regulators parsed in terms of what an organism can sense about itself and its environment by defining entities, their sensors and the sensed properties. Entities include small molecules (ATP, ions, metabolites, etc.), macromolecules (individual proteins, RNAs, polysaccharides, etc.) and assemblies of molecules. While concentration may be the only relevant property measured by sensors for small molecules, multiple properties that include concentration, sequence, conformation and modification may all be measured for macromolecules and assemblies. Each configuration of these entities and sensors that is recreated in successive generations in a given environment thus specifies a potentially vast amount of information driving complex development in each generation. This entity-sensor-property framework explains how sensors limit the number of distinguishable states, how distinct molecular configurations can be functionally equivalent and how regulation of sensors prevents detection of some perturbations. Overall, this framework is a useful guide for understanding how life evolves and how the storage of information has itself evolved with complexity since before the origin of life.
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Affiliation(s)
- Antony M. Jose
- Department of Cell Biology and Molecular Genetics, University of Maryland, Room 2136, Bioscience Research Building (Building #413), College Park, MD 20742, USA
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40
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Still Minding the Gap? Reflecting on Transitions between Concepts of Information in Varied Domains. INFORMATION 2020. [DOI: 10.3390/info11020071] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
This conceptual paper, a contribution to the tenth anniversary Special Issue of Information, gives a cross-disciplinary review of general and unified theories of information. A selective literature review is used to update a 2013 article on bridging the gaps between conceptions of information in different domains, including material from the physical and biological sciences, from the humanities and social sciences including library and information science, and from philosophy. A variety of approaches and theories are reviewed, including those of Brenner, Brier, Burgin and Wu, Capurro, Cárdenas-García and Ireland, Hidalgo, Hofkirchner, Kolchinsky and Wolpert, Floridi, Mingers and Standing, Popper, and Stonier. The gaps between disciplinary views of information remain, although there has been progress, and increasing interest, in bridging them. The solution is likely to be either a general theory of sufficient flexibility to cope with multiple meanings of information, or multiple and distinct theories for different domains, but with a complementary nature, and ideally boundary spanning concepts.
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41
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Kolchinsky A, Corominas-Murtra B. Decomposing information into copying versus transformation. J R Soc Interface 2020; 17:20190623. [PMID: 31964273 DOI: 10.1098/rsif.2019.0623] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
In many real-world systems, information can be transmitted in two qualitatively different ways: by copying or by transformation. Copying occurs when messages are transmitted without modification, e.g. when an offspring receives an unaltered copy of a gene from its parent. Transformation occurs when messages are modified systematically during transmission, e.g. when mutational biases occur during genetic replication. Standard information-theoretic measures do not distinguish these two modes of information transfer, although they may reflect different mechanisms and have different functional consequences. Starting from a few simple axioms, we derive a decomposition of mutual information into the information transmitted by copying versus the information transmitted by transformation. We begin with a decomposition that applies when the source and destination of the channel have the same set of messages and a notion of message identity exists. We then generalize our decomposition to other kinds of channels, which can involve different source and destination sets and broader notions of similarity. In addition, we show that copy information can be interpreted as the minimal work needed by a physical copying process, which is relevant for understanding the physics of replication. We use the proposed decomposition to explore a model of amino acid substitution rates. Our results apply to any system in which the fidelity of copying, rather than simple predictability, is of critical relevance.
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42
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Affiliation(s)
- Francesco Avanzini
- Complex Systems and Statistical Mechanics, Physics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg City, Luxembourg
| | - Gianmaria Falasco
- Complex Systems and Statistical Mechanics, Physics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg City, Luxembourg
| | - Massimiliano Esposito
- Complex Systems and Statistical Mechanics, Physics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg City, Luxembourg
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43
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Levin M. The Computational Boundary of a "Self": Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition. Front Psychol 2019; 10:2688. [PMID: 31920779 PMCID: PMC6923654 DOI: 10.3389/fpsyg.2019.02688] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Accepted: 11/14/2019] [Indexed: 12/12/2022] Open
Abstract
All epistemic agents physically consist of parts that must somehow comprise an integrated cognitive self. Biological individuals consist of subunits (organs, cells, and molecular networks) that are themselves complex and competent in their own native contexts. How do coherent biological Individuals result from the activity of smaller sub-agents? To understand the evolution and function of metazoan creatures' bodies and minds, it is essential to conceptually explore the origin of multicellularity and the scaling of the basal cognition of individual cells into a coherent larger organism. In this article, I synthesize ideas in cognitive science, evolutionary biology, and developmental physiology toward a hypothesis about the origin of Individuality: "Scale-Free Cognition." I propose a fundamental definition of an Individual based on the ability to pursue goals at an appropriate level of scale and organization and suggest a formalism for defining and comparing the cognitive capacities of highly diverse types of agents. Any Self is demarcated by a computational surface - the spatio-temporal boundary of events that it can measure, model, and try to affect. This surface sets a functional boundary - a cognitive "light cone" which defines the scale and limits of its cognition. I hypothesize that higher level goal-directed activity and agency, resulting in larger cognitive boundaries, evolve from the primal homeostatic drive of living things to reduce stress - the difference between current conditions and life-optimal conditions. The mechanisms of developmental bioelectricity - the ability of all cells to form electrical networks that process information - suggest a plausible set of gradual evolutionary steps that naturally lead from physiological homeostasis in single cells to memory, prediction, and ultimately complex cognitive agents, via scale-up of the basic drive of infotaxis. Recent data on the molecular mechanisms of pre-neural bioelectricity suggest a model of how increasingly sophisticated cognitive functions emerge smoothly from cell-cell communication used to guide embryogenesis and regeneration. This set of hypotheses provides a novel perspective on numerous phenomena, such as cancer, and makes several unique, testable predictions for interdisciplinary research that have implications not only for evolutionary developmental biology but also for biomedicine and perhaps artificial intelligence and exobiology.
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Affiliation(s)
- Michael Levin
- Allen Discovery Center at Tufts University, Medford, MA, United States
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, United States
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44
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Jeffery K, Pollack R, Rovelli C. On the Statistical Mechanics of Life: Schrödinger Revisited. ENTROPY 2019. [PMCID: PMC7514554 DOI: 10.3390/e21121211] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
We study the statistical underpinnings of life, in particular its increase in order and complexity over evolutionary time. We question some common assumptions about the thermodynamics of life. We recall that contrary to widespread belief, even in a closed system entropy growth can accompany an increase in macroscopic order. We view metabolism in living things as microscopic variables directly driven by the second law of thermodynamics, while viewing the macroscopic variables of structure, complexity and homeostasis as mechanisms that are entropically favored because they open channels for entropy to grow via metabolism. This perspective reverses the conventional relation between structure and metabolism, by emphasizing the role of structure for metabolism rather than the converse. Structure extends in time, preserving information along generations, particularly in the genetic code, but also in human culture. We argue that increasing complexity is an inevitable tendency for systems with these dynamics and explain this with the notion of metastable states, which are enclosed regions of the phase-space that we call “bubbles,” and channels between these, which are discovered by random motion of the system. We consider that more complex systems inhabit larger bubbles (have more available states), and also that larger bubbles are more easily entered and less easily exited than small bubbles. The result is that the system entropically wanders into ever-larger bubbles in the foamy phase space, becoming more complex over time. This formulation makes intuitive why the increase in order/complexity over time is often stepwise and sometimes collapses catastrophically, as in biological extinction.
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Affiliation(s)
- Kate Jeffery
- Institute of Behavioural Neuroscience, University College, London WC1H 0AP, UK;
| | - Robert Pollack
- Biological Sciences, Columbia University, 749 Mudd, Mailcode 2419, NY 10027, USA;
| | - Carlo Rovelli
- Centre de Physique Théorique, Aix-Marseille Université, Université de Toulon, CNRS, 13009 Marseille, France
- Perimeter Institute, 31 Caroline Street North, Waterloo, ON N2L 2Y5, Canada
- Rotman Institute of Philosophy, 1151 Richmond St. North, London, ON N6A 5B7, Canada
- Correspondence:
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45
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Abstract
The Bayesian brain hypothesis, predictive processing, and variational free energy minimisation are typically used to describe perceptual processes based on accurate generative models of the world. However, generative models need not be veridical representations of the environment. We suggest that they can (and should) be used to describe sensorimotor relationships relevant for behaviour rather than precise accounts of the world.
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46
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Abstract
The dynamical evolution of a system of interacting elements can be predicted in terms of its elementary constituents and their interactions, or in terms of the system’s global state transitions. For this reason, systems with equivalent global dynamics are often taken to be equivalent for all relevant purposes. Nevertheless, such systems may still vary in their causal composition—the way mechanisms within the system specify causes and effects over different subsets of system elements. We demonstrate this point based on a set of small discrete dynamical systems with reversible dynamics that cycle through all their possible states. Our analysis elucidates the role of composition within the formal framework of integrated information theory. We show that the global dynamical and information-theoretic capacities of reversible systems can be maximal even though they may differ, quantitatively and qualitatively, in the information that their various subsets specify about each other (intrinsic information). This can be the case even for a system and its time-reversed equivalent. Due to differences in their causal composition, two systems with equivalent global dynamics may still differ in their capacity for autonomy, agency, and phenomenology.
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48
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de la Escosura A. The Informational Substrate of Chemical Evolution: Implications for Abiogenesis. Life (Basel) 2019; 9:E66. [PMID: 31398942 PMCID: PMC6789672 DOI: 10.3390/life9030066] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Revised: 07/26/2019] [Accepted: 08/05/2019] [Indexed: 12/11/2022] Open
Abstract
A key aspect of biological evolution is the capacity of living systems to process information, coded in deoxyribonucleic acid (DNA), and used to direct how the cell works. The overall picture that emerges today from fields such as developmental, synthetic, and systems biology indicates that information processing in cells occurs through a hierarchy of genes regulating the activity of other genes through complex metabolic networks. There is an implicit semiotic character in this way of dealing with information, based on functional molecules that act as signs to achieve self-regulation of the whole network. In contrast to cells, chemical systems are not thought of being able to process information, yet they must have preceded biological organisms, and evolved into them. Hence, there must have been prebiotic molecular assemblies that could somehow process information, in order to regulate their own constituent reactions and supramolecular organization processes. The purpose of this essay is then to reflect about the distinctive features of information in living and non-living matter, and on how the capacity of biological organisms for information processing was possibly rooted in a particular type of chemical systems (here referred to as autonomous chemical systems), which could self-sustain and reproduce through organizational closure of their molecular building blocks.
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Affiliation(s)
- Andrés de la Escosura
- Department of Organic Chemistry, Universidad Autónoma of Madrid, Cantoblanco Campus, 28049 Madrid, Spain.
- Department of Organic Chemistry, Institute for Advanced Research in Chemistry (IAdChem), Cantoblanco Campus, 28049 Madrid, Spain.
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49
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Thermodynamics of Majority-Logic Decoding in Information Erasure. ENTROPY 2019; 21:e21030284. [PMID: 33266999 PMCID: PMC7514764 DOI: 10.3390/e21030284] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 02/25/2019] [Accepted: 03/11/2019] [Indexed: 01/31/2023]
Abstract
We investigate the performance of majority-logic decoding in both reversible and finite-time information erasure processes performed on macroscopic bits that contain N microscopic binary units. While we show that for reversible erasure protocols single-unit transformations are more efficient than majority-logic decoding, the latter is found to offer several benefits for finite-time erasure processes: Both the minimal erasure duration for a given erasure and the minimal erasure error for a given erasure duration are reduced, if compared to a single unit. Remarkably, the majority-logic decoding is also more efficient in both the small-erasure error and fast-erasure region. These benefits are also preserved under the optimal erasure protocol that minimizes the dissipated heat. Our work therefore shows that majority-logic decoding can lift the precision-speed-efficiency trade-off in information erasure processes.
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50
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Baltieri M, Buckley CL. PID Control as a Process of Active Inference with Linear Generative Models. ENTROPY (BASEL, SWITZERLAND) 2019; 21:E257. [PMID: 33266972 PMCID: PMC7514737 DOI: 10.3390/e21030257] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Revised: 02/20/2019] [Accepted: 03/03/2019] [Indexed: 11/16/2022]
Abstract
In the past few decades, probabilistic interpretations of brain functions have become widespread in cognitive science and neuroscience. In particular, the free energy principle and active inference are increasingly popular theories of cognitive functions that claim to offer a unified understanding of life and cognition within a general mathematical framework derived from information and control theory, and statistical mechanics. However, we argue that if the active inference proposal is to be taken as a general process theory for biological systems, it is necessary to understand how it relates to existing control theoretical approaches routinely used to study and explain biological systems. For example, recently, PID (Proportional-Integral-Derivative) control has been shown to be implemented in simple molecular systems and is becoming a popular mechanistic explanation of behaviours such as chemotaxis in bacteria and amoebae, and robust adaptation in biochemical networks. In this work, we will show how PID controllers can fit a more general theory of life and cognition under the principle of (variational) free energy minimisation when using approximate linear generative models of the world. This more general interpretation also provides a new perspective on traditional problems of PID controllers such as parameter tuning as well as the need to balance performances and robustness conditions of a controller. Specifically, we then show how these problems can be understood in terms of the optimisation of the precisions (inverse variances) modulating different prediction errors in the free energy functional.
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Affiliation(s)
- Manuel Baltieri
- EASY Group—Sussex Neuroscience, Department of Informatics, University of Sussex, Brighton BN1 9RH, UK
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