Embodied cognition and circular causality: on the role of constitutive autonomy in the reciprocal coupling of perception and action

Living cells and biological mechanisms as prototypes for developing chemical artificial intelligence

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.

Adapting Ourselves, Instead of the Environment: An Inquiry into Human Enhancement for Function and Beyond

Technology enables humans not only to adapt their environment to their needs but also to modify themselves. Means of Human Enhancement - embodied technologies to improve the human body's capabilities or to create a new one - are the designated means of adapting ourselves instead of the environment. The debate about these technologies is typically fought on ethical soil. However, alarmist, utopian, and science fiction scenarios distract from the fact that Human Enhancement is a historical and pervasive phenomenon incorporated into many everyday practices. In the vein of disentangling conceptual difficulties, we claim that means of Human Enhancement are either physiologically or psychologically embodied, rendering the merging with the human user their most defining aspect. To fulfill its purpose, an enhancement must pass the test-in-the-world, i.e., assisting with effective engagement with a dynamic world. Even if failing in this regard: Human Enhancement is the fundamental and semi-targeted process of changing the users relationship with the world through the physical or psychological embodiment of a hitherto external object and/or change of one's body. This can potentially change the notion of being human. Drawing on a rich body of theoretical and empirical literature, we aim to provide a nuanced analysis of the transformative nature of this phenomenon in close proximity to human practice. Stakeholders are invited to apply the theory presented here to interrogate their perspective on technology in general and Human Enhancement in particular.

Self-Improvising Memory: A Perspective on Memories as Agential, Dynamically Reinterpreting Cognitive Glue

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.

Artificial cognition vs. artificial intelligence for next-generation autonomous robotic agents

The trend in industrial/service robotics is to develop robots that can cooperate with people, interacting with them in an autonomous, safe and purposive way. These are the fundamental elements characterizing the fourth and the fifth industrial revolutions (4IR, 5IR): the crucial innovation is the adoption of intelligent technologies that can allow the development of cyber-physical systems, similar if not superior to humans. The common wisdom is that intelligence might be provided by AI (Artificial Intelligence), a claim that is supported more by media coverage and commercial interests than by solid scientific evidence. AI is currently conceived in a quite broad sense, encompassing LLMs and a lot of other things, without any unifying principle, but self-motivating for the success in various areas. The current view of AI robotics mostly follows a purely disembodied approach that is consistent with the old-fashioned, Cartesian mind-body dualism, reflected in the software-hardware distinction inherent to the von Neumann computing architecture. The working hypothesis of this position paper is that the road to the next generation of autonomous robotic agents with cognitive capabilities requires a fully brain-inspired, embodied cognitive approach that avoids the trap of mind-body dualism and aims at the full integration of Bodyware and Cogniware. We name this approach Artificial Cognition (ACo) and ground it in Cognitive Neuroscience. It is specifically focused on proactive knowledge acquisition based on bidirectional human-robot interaction: the practical advantage is to enhance generalization and explainability. Moreover, we believe that a brain-inspired network of interactions is necessary for allowing humans to cooperate with artificial cognitive agents, building a growing level of personal trust and reciprocal accountability: this is clearly missing, although actively sought, in current AI. The ACo approach is a work in progress that can take advantage of a number of research threads, some of them antecedent the early attempts to define AI concepts and methods. In the rest of the paper we will consider some of the building blocks that need to be re-visited in a unitary framework: the principles of developmental robotics, the methods of action representation with prospection capabilities, and the crucial role of social interaction.

Competency in Navigating Arbitrary Spaces as an Invariant for Analyzing Cognition in Diverse Embodiments

One of the most salient features of life is its capacity to handle novelty and namely to thrive and adapt to new circumstances and changes in both the environment and internal components. An understanding of this capacity is central to several fields: the evolution of form and function, the design of effective strategies for biomedicine, and the creation of novel life forms via chimeric and bioengineering technologies. Here, we review instructive examples of living organisms solving diverse problems and propose competent navigation in arbitrary spaces as an invariant for thinking about the scaling of cognition during evolution. We argue that our innate capacity to recognize agency and intelligence in unfamiliar guises lags far behind our ability to detect it in familiar behavioral contexts. The multi-scale competency of life is essential to adaptive function, potentiating evolution and providing strategies for top-down control (not micromanagement) to address complex disease and injury. We propose an observer-focused viewpoint that is agnostic about scale and implementation, illustrating how evolution pivoted similar strategies to explore and exploit metabolic, transcriptional, morphological, and finally 3D motion spaces. By generalizing the concept of behavior, we gain novel perspectives on evolution, strategies for system-level biomedical interventions, and the construction of bioengineered intelligences. This framework is a first step toward relating to intelligence in highly unfamiliar embodiments, which will be essential for progress in artificial intelligence and regenerative medicine and for thriving in a world increasingly populated by synthetic, bio-robotic, and hybrid beings.

Viruses as Living Systems—A Metacybernetic View

The debate over whether viruses are living organisms tends to be paradigmatically determined. The metabolic paradigm denies that they are, while new research evidences the opposite. The purpose of this paper is to deliver a generic model for viral contexts that explains why viruses are alive. It will take a systems biology approach, with a qualitative part (using metacybernetics) to provide deeper explanations of viral contexts, and a quantitative part (using Fisher Information deriving from the variational principle of Extreme Physical Information) which is in principle able to take measurements and predict outcomes. The modelling process provides an extended view of the epigenetic processes of viruses. The generic systems biology model will depict viruses as autonomous entities with metaphysical processes of autopoietic self-organisation and adaptation, enabling them to maintain their physical viability and hence, within their populations, mutate and evolve. The autopoietic epigenetic processes are shown to describe their capability to change, and these are both qualitatively and quantitatively explored, the latter providing an approach to make measurements of physical phenomena under uncertainty. Viruses maintain their fitness when they are able to maintain their stability, and this is indicated by information flow efficacy. A brief case study is presented on the COVID-19 virus from the perspective that it is a living system, and this includes outcome predictions given Fisher Information conditions for known contexts.

The Neurorobotics Platform Robot Designer: Modeling Morphologies for Embodied Learning Experiments

The more we investigate the principles of motion learning in biological systems, the more we reveal the central role that body morphology plays in motion execution. Not only does anatomy define the kinematics and therefore the complexity of possible movements, but it now becomes clear that part of the computation required for motion control is offloaded to body dynamics (a phenomenon referred to as “Morphological Computation.”) Consequentially, a proper design of body morphology is essential to carry out meaningful simulations on motor control of robotic and musculoskeletal systems. The design should not be fixed for simulation experiments beforehand, but is a central research aspect in every motion learning experiment that requires continuous adaptation during the experimental phase. We herein introduce a plugin for the 3D modeling suite Blender that enables researchers to design morphologies for simulation experiments in, particularly but not restricted to, the Neurorobotics Platform. We include design capabilities for both musculoskeletal bodies, as well as robotic systems in the Robot Designer. Thereby, we hope to not only foster understanding of biological motions and enabling better robot designs, but enabling true Neurorobotic experiments that may consist of biomimetic models such as tendon-driven robot as a mix of both or a transition between both biology and technology. This plugin helps researchers design and parameterize models with a Graphical User Interface and thus simplifies and speeds up the overall design process.

Artificial Interactionism: Avoiding Isolating Perception From Cognition in AI

We discuss the influence upon the fields of robotics and AI of the manner one conceives the relationships between artificial agents' perception, cognition, and action. We shed some light upon a widespread paradigm we call the isolated perception paradigm that addresses perception as isolated from cognition and action. By mobilizing the resources of philosophy (phenomenology and epistemology) and cognitive sciences, and by drawing on recent approaches in AI, we explore what it could mean for robotics and AI to take distance from the isolated perception paradigm. We argue that such a renouncement opens interesting ways to explore the possibilities for designing artificial agents with intrinsic motivations and constitutive autonomy. We then propose Artificial Interactionism, our approach that escapes the isolated perception paradigm by drawing on the inversion of the interaction cycle. When the interaction cycle is inverted, input data are not percepts directly received from the environment, but outcomes of control loops. Perception is not received from sensors in isolation from cognition but is actively constructed by the cognitive architecture through interaction. We give an example implementation of artificial interactionism that demonstrates basic intrinsically motivated learning behavior in a dynamic simulated environment.

A physiological and dynamical systems model of stress

Stress responses vary drastically for a given set of stimuli, individuals, or points in time. A potential source of this variance that is not well characterized arises from the theory of stress as a dynamical system, which implies a complex, nonlinear relationship between environmental/situational inputs and the development/experience of stress. In this framework, stress vs. non-stress states exist as attractor basins in a physiologic phase space. Here, we develop a model of stress as a dynamical system by coupling closed loop physiologic control to a dynamic oscillator in an attractor landscape. By characterizing the evolution of this model through phase space, we demonstrate strong sensitivity to the parameters controlling the dynamics and demonstrate multiple features of stress responses found in current research, implying that these parameters may contribute to a significant source of variability observed in empiric stress research.

Living Things Are Not (20th Century) Machines: Updating Mechanism Metaphors in Light of the Modern Science of Machine Behavior

One of the most useful metaphors for driving scientific and engineering progress has been that of the “machine.” Much controversy exists about the applicability of this concept in the life sciences. Advances in molecular biology have revealed numerous design principles that can be harnessed to understand cells from an engineering perspective, and build novel devices to rationally exploit the laws of chemistry, physics, and computation. At the same time, organicists point to the many unique features of life, especially at larger scales of organization, which have resisted decomposition analysis and artificial implementation. Here, we argue that much of this debate has focused on inessential aspects of machines – classical properties which have been surpassed by advances in modern Machine Behavior and no longer apply. This emerging multidisciplinary field, at the interface of artificial life, machine learning, and synthetic bioengineering, is highlighting the inadequacy of existing definitions. Key terms such as machine, robot, program, software, evolved, designed, etc., need to be revised in light of technological and theoretical advances that have moved past the dated philosophical conceptions that have limited our understanding of both evolved and designed systems. Moving beyond contingent aspects of historical and current machines will enable conceptual tools that embrace inevitable advances in synthetic and hybrid bioengineering and computer science, toward a framework that identifies essential distinctions between fundamental concepts of devices and living agents. Progress in both theory and practical applications requires the establishment of a novel conception of “machines as they could be,” based on the profound lessons of biology at all scales. We sketch a perspective that acknowledges the remarkable, unique aspects of life to help re-define key terms, and identify deep, essential features of concepts for a future in which sharp boundaries between evolved and designed systems will not exist.

Static internal representation of dynamic situations reveals time compaction in human cognition

Introduction

The human brain has evolved under the constraint of survival in complex dynamic situations. It makes fast and reliable decisions based on internal representations of the environment. Whereas neural mechanisms involved in the internal representation of space are becoming known, entire spatiotemporal cognition remains a challenge. Growing experimental evidence suggests that brain mechanisms devoted to spatial cognition may also participate in spatiotemporal information processing.

Objectives

The time compaction hypothesis postulates that the brain represents both static and dynamic situations as purely static maps. Such an internal reduction of the external complexity allows humans to process time-changing situations in real-time efficiently. According to time compaction, there may be a deep inner similarity between the representation of conventional static and dynamic visual stimuli. Here, we test the hypothesis and report the first experimental evidence of time compaction in humans.

Methods

We engaged human subjects in a discrimination-learning task consisting in the classification of static and dynamic visual stimuli. When there was a hidden correspondence between static and dynamic stimuli due to time compaction, the learning performance was expected to be modulated. We studied such a modulation experimentally and by a computational model.

Results

The collected data validated the predicted learning modulation and confirmed that time compaction is a salient cognitive strategy adopted by the human brain to process time-changing situations. Mathematical modelling supported the finding. We also revealed that men are more prone to exploit time compaction in accordance with the context of the hypothesis as a cognitive basis for survival.

Conclusions

The static internal representation of dynamic situations is a human cognitive mechanism involved in decision-making and strategy planning to cope with time-changing environments. The finding opens a new venue to understand how humans efficiently interact with our dynamic world and thrive in nature.

An organisational systems-biology view of viruses explains why they are not alive

Whether or not viruses are alive remains unsettled. Discoveries of giant viruses with translational genes and large genomes have kept the debate active. Here, a fresh approach is introduced, based on the organisational definition of life from within systems biology. It views living as a circular process of self-organisation and self-construction which is 'closed to efficient causation'. How information combines with force to fabricate and organise environmentally obtained materials, given an energy source, is here explained as a physical embodiment of informational constraint. Comparing a general virus replication cycle with Rosen's (M,R)-system shows it to be linear, rather than closed. Some viruses contribute considerable organisational information, but so far none is known to supply all required, nor the material nor energy necessary to complete their replication cycle. As a result, no known virus replication cycle is closed to efficient causation: unlike cellular obligate parasites, viruses do not match the causal structure of an (M,R)-system. Analysis based in identifying a Markov blanket in causal structure proved inconclusive, but using Integrated Information Theory on a Boolean representation, it was possible to show that the causal structure of a virocell is not different from that of the host cell.

The Circularity of the Embodied Mind

From an embodied and enactive point of view, the mind-body problem has been reformulated as the relation between the lived or subject body on the one hand and the physiological or object body on the other ("body-body problem"). The aim of the paper is to explore the concept of circularity as a means of explaining the relation between the phenomenology of lived experience and the dynamics of organism-environment interactions. This concept of circularity also seems suitable for connecting enactive accounts with ecological psychology. It will be developed in a threefold way: (1) As the circular structure of embodiment, which manifests itself (a) in the homeostatic cycles between the brain and body and (b) in the sensorimotor cycles between the brain, body, and environment. This includes the interdependence of an organism's dispositions of sense-making and the affordances of the environment. (2) As the circular causality, which characterizes the relation between parts and whole within the living organism as well as within the organism-environment system. (3) As the circularity of process and structure in development and learning. Here, it will be argued that subjective experience constitutes a process of sense-making that implies (neuro-)physiological processes so as to form modified neuronal structures, which in turn enable altered future interactions. On this basis, embodied experience may ultimately be conceived as the integration of brain-body and body-environment interactions, which has a top-down, formative, or ordering effect on physiological processes. This will serve as an approach to a solution of the body-body problem.

Science-Driven Societal Transformation, Part I: Worldview

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.

Exploiting Bi-Directional Self-Organizing Tendencies in Team Sports: The Role of the Game Model and Tactical Principles of Play

Research has revealed how inherent self-organizing tendencies in athletes and sports teams can be exploited to facilitate emergence of dynamical patterns in synergy formation in sports teams. Here, we discuss how game models, and associated tactical principles of play, may be implemented to constrain co-existing global-to-local and local-to-global self-organization tendencies in team sports players during training and performance. Understanding how to harness the continuous interplay between these co-existing, bi-directional, and coordination tendencies is key to shaping system behaviors in sports training. Training programs are traditionally dominated by designs, which shape the self-organizing tendencies of players and teams at a global-to-local scale by coaches imposing a tactical/strategical plan with associated tactical principles of play. Nevertheless, recent research suggests that performers also need to be provided with opportunities to explore self-organizing tendencies that emerge at the local-to-global scale in training. This directional tendency in synergy formation can be facilitated by players being given opportunities to actively explore different adaptive and innovative performance solutions, coherent with principles of play circumscribed in an overarching game model. Developing methods (coaching sessions rooted on principles of dynamical systems theory that foment the development of such local-to-global relations) to exploit the continuous interplay between these co-existing tendencies within sports teams may promote more effective and efficient athlete skill training programs, in addition to enhancing performance.

Emotions in Robots: Embodied Interaction in Social and Non-Social Environments

Whether they are considered discrete or dimensional, emotions are ’embodied’ phenomena [...]

Recent Technology-Aided Programs to Support Adaptive Responses, Functional Activities, and Leisure and Communication in People With Significant Disabilities

This paper presents an overview of recent technology-aided programs (i. e., technology-aided support tools) designed to help people with significant disabilities (a) engage in adaptive responses, functional activities, and leisure and communication, and thus (b) interact with their physical and social environment and improve their performance/achievement. In order to illustrate the support tools, the paper provides an overview of recent studies aimed at developing and assessing those tools. The paper also examines the tools' accessibility and usability, and comments on possible ways of modifying and advancing them to improve their impact. The tools taken into consideration concern, among others, (a) microswitches linked to computer systems, and aimed at promoting (i.e., through positive stimulation) minimal responses or functional body movements in individuals with intellectual disabilities and motor impairments; (b) computer systems, tablets, or smartphones aimed at supporting functional activity engagement of individuals with intellectual disabilities or Alzheimer's disease; and (c) microswitches with computer-aided systems, elaborate communication devices, and specifically arranged smartphones or tablets, directed at promoting leisure, communication, or both.

Do Not Neglect the Body and Action: The Emergence of Embodiment Approaches to Understanding Human Development

It is becoming clear that to truly understand what it is to be human, focusing scientific efforts on the mind alone is insufficient. We are embodied minds, living and acting in a world full of meaningful things. In this article, we discuss how science has been informed by important research insights into the close relationship between the body, the mind, and the world. These interactions can be translated into embodied perspectives of human development. We provide evidence that perception, cognition, emotion, human relations, and behavior are grounded in our bodies from the beginning of our lives. From this perspective, the body cannot be assumed to be simply an effector for cognition or an instrument for collecting information for the brain. This comprehensive review and debate of embodied-related literature is accompanied by the identification of theoretical challenges and practical applications that will shape research for years to come.

CONCEPT ANALYSIS STRATEGIES FOR THE DEVELOPMENT OF MIDDLE-RANGE NURSING THEORIES

ABSTRACT Objective: to reflect on strengths and limitations of the concept analysis strategies as resources for the development of middle-range nursing theories. Method: a reflection study of metatheoretical nature. Results: strategies for concept analysis for the development of middle-range nursing theories are presented. The philosophical foundations of concepts and their interface with the analytical procedures were presented. It has been found that Nursing uses three approaches for concept analysis: adapted Wilsonian, evolutionary and pragmatic utility. The concept analysis strategy was illustrated by the Interactive Theory of Breastfeeding. Conclusion: concept analysis strategies have been employed in nursing to develop theories and to refine the concepts and terminologies used in research and practice. Despite their widespread use, there is still great diversity of methods used and some uncertainties that hinder their implementation.

Social Cognition for Human-Robot Symbiosis-Challenges and Building Blocks

The next generation of robot companions or robot working partners will need to satisfy social requirements somehow similar to the famous laws of robotics envisaged by Isaac Asimov time ago (Asimov, 1942). The necessary technology has almost reached the required level, including sensors and actuators, but the cognitive organization is still in its infancy and is only partially supported by the current understanding of brain cognitive processes. The brain of symbiotic robots will certainly not be a “positronic” replica of the human brain: probably, the greatest part of it will be a set of interacting computational processes running in the cloud. In this article, we review the challenges that must be met in the design of a set of interacting computational processes as building blocks of a cognitive architecture that may give symbiotic capabilities to collaborative robots of the next decades: (1) an animated body-schema; (2) an imitation machinery; (3) a motor intentions machinery; (4) a set of physical interaction mechanisms; and (5) a shared memory system for incremental symbiotic development. We would like to stress that our approach is totally un-hierarchical: the five building blocks of the shared cognitive architecture are fully bi-directionally connected. For example, imitation and intentional processes require the “services” of the animated body schema which, on the other hand, can run its simulations if appropriately prompted by imitation and/or intention, with or without physical interaction. Successful experiences can leave a trace in the shared memory system and chunks of memory fragment may compete to participate to novel cooperative actions. And so on and so forth. At the heart of the system is lifelong training and learning but, different from the conventional learning paradigms in neural networks, where learning is somehow passively imposed by an external agent, in symbiotic robots there is an element of free choice of what is worth learning, driven by the interaction between the robot and the human partner. The proposed set of building blocks is certainly a rough approximation of what is needed by symbiotic robots but we believe it is a useful starting point for building a computational framework.

How Organisms Gained Causal Independence and How It Might Be Quantified

Two broad features are jointly necessary for autonomous agency: organisational closure and the embodiment of an objective-function providing a ‘goal’: so far only organisms demonstrate both. Organisational closure has been studied (mostly in abstract), especially as cell autopoiesis and the cybernetic principles of autonomy, but the role of an internalised ‘goal’ and how it is instantiated by cell signalling and the functioning of nervous systems has received less attention. Here I add some biological ‘flesh’ to the cybernetic theory and trace the evolutionary development of step-changes in autonomy: (1) homeostasis of organisationally closed systems; (2) perception-action systems; (3) action selection systems; (4) cognitive systems; (5) memory supporting a self-model able to anticipate and evaluate actions and consequences. Each stage is characterised by the number of nested goal-directed control-loops embodied by the organism, summarised as will-nestedness N. Organism tegument, receptor/transducer system, mechanisms of cellular and whole-organism re-programming and organisational integration, all contribute to causal independence.

CONCLUSION

organisms are cybernetic phenomena whose identity is created by the information structure of the highest level of causal closure (maximum N), which has increased through evolution, leading to increased causal independence, which might be quantifiable by ‘Integrated Information Theory’ measures.

Reconsidering the International Association for the Study of Pain definition of pain

INTRODUCTION

The definition of pain promulgated by the International Association for the Study of Pain (IASP) is widely accepted as a pragmatic characterisation of that human experience. Although the Notes that accompany it characterise pain as "always subjective," the IASP definition itself fails to sufficiently integrate phenomenological aspects of pain.

METHODS

This essay reviews the historical development of the IASP definition, and the commentaries and suggested modifications to it over almost 40 years. Common factors of pain experience identified in phenomenological studies are described, together with theoretical insights from philosophy and biology.

RESULTS

A fuller understanding of the pain experience and of the clinical care of those experiencing pain is achievable through greater attention to the phenomenology of pain, the social "intersubjective space" in which pain occurs, and the limitations of language.

CONCLUSION

Based on these results, a revised definition of pain is offered: Pain is a mutually recognizable somatic experience that reflects a person's apprehension of threat to their bodily or existential integrity.

The Clinical Concept of Opioid Addiction Since 1877: Still Wanting After All These Years

In 1877, the psychiatrist Edward Levinstein authored the first monograph on opioid addiction. The prevalence of opioid addiction prior to his publication had risen in several countries including England, France and Germany. He was the first to call it an illness, but doubted that it was a mental illness because the impairment of volition appeared to be restricted to opioid use: it was not pervasive, since it did not extend to other aspects of the individuals' life. While there has been huge progress in understanding the underlying neurobiological mechanisms, there has been little progress in the clinical psychopathology of addiction and in understanding how it relates to these neurobiological mechanisms. A focus on cravings has limited the exploration of other important aspects such as anosognosia and addiction-related behaviors like smuggling opioids into treatment and supporting the continued provision of co-patients. These behaviors are usually considered secondary reactions, but in clinical practice they appear to be central to addiction, indicating that an improved understanding of the complexity of the disorder is needed. We propose to consider an approach that takes into account the embodied, situated, dynamic, and phenomenological aspects of mental processes. Addiction in this context can be conceptualized as a habit, understood as a distributed network of mental, behavioral, and social processes, which not only shapes the addict's perceptions and actions, but also has a tendency to self-maintain. Such an approach may help to develop and integrate psychopathological and neurobiological research and practice of addictions.

The body of knowledge: On the role of the living body in grounding embodied cognition

Embodied cognition is a hot topic in both cognitive science and AI, despite the fact that there still is relatively little consensus regarding what exactly constitutes 'embodiment'. While most embodied AI and cognitive robotics research views the body as the physical/sensorimotor interface that allows to ground computational cognitive processes in sensorimotor interactions with the environment, more biologically-based notions of embodied cognition emphasize the fundamental role that the living body - and more specifically its homeostatic/allostatic self-regulation - plays in grounding both sensorimotor interactions and embodied cognitive processes. Adopting the latter position - a multi-tiered affectively embodied view of cognition in living systems - it is further argued that modeling organisms as layered networks of bodily self-regulation mechanisms can make significant contributions to our scientific understanding of embodied cognition.

Introducing a Pictographic Language for Envisioning a Rich Variety of Enactive Systems with Different Degrees of Complexity

Notwithstanding the considerable amount of progress that has been made in recent years, the parallel fields of cognitive science and cognitive systems lack a unifying methodology for describing, understanding, simulating and implementing advanced cognitive behaviours. Growing interest in ‘enactivism’ - as pioneered by the Chilean biologists Humberto Maturana and Francisco Varela - may lead to new perspectives in these areas, but a common framework for expressing many of the key concepts is still missing. This paper attempts to lay a tentative foundation in that direction by extending Maturana and Varela's pictographic depictions of autopoietic unities to create a rich visual language for envisioning a wide range of enactive systems - natural or artificial - with different degrees of complexity. It is shown how such a diagrammatic taxonomy can help in the comprehension of important relationships between a variety of complex concepts from a pan-theoretic perspective. In conclusion, it is claimed that visual language is not only valuable for teaching and learning, but also offers important insights into the design and implementation of future advanced robotic systems.