Order-Stability in Complex Biological, Social, and AI-Systems from Quantum Information Theory

Open Systems, Quantum Probability, and Logic for Quantum-like Modeling in Biology, Cognition, and Decision-Making

The aim of this review is to highlight the possibility of applying the mathematical formalism and methodology of quantum theory to model behavior of complex biosystems, from genomes and proteins to animals, humans, and ecological and social systems. Such models are known as quantum-like, and they should be distinguished from genuine quantum physical modeling of biological phenomena. One of the distinguishing features of quantum-like models is their applicability to macroscopic biosystems or, to be more precise, to information processing in them. Quantum-like modeling has its basis in quantum information theory, and it can be considered one of the fruits of the quantum information revolution. Since any isolated biosystem is dead, modeling of biological as well as mental processes should be based on the theory of open systems in its most general form-the theory of open quantum systems. In this review, we explain its applications to biology and cognition, especially theory of quantum instruments and the quantum master equation. We mention the possible interpretations of the basic entities of quantum-like models with special interest given to QBism, as it may be the most useful interpretation.

Constrained disorder principle-based variability is fundamental for biological processes: Beyond biological relativity and physiological regulatory networks

The constrained disorder principle (CDP) defines systems based on their degree of disorder bounded by dynamic boundaries. The principle explains stochasticity in living and non-living systems. Denis Noble described the importance of stochasticity in biology, emphasizing stochastic processes at molecular, cellular, and higher levels in organisms as having a role beyond simple noise. The CDP and Noble's theories (NT) claim that biological systems use stochasticity. This paper presents the CDP and NT, discussing common notions and differences between the two theories. The paper presents the CDP-based concept of taking the disorder beyond its role in nature to correct malfunctions of systems and improve the efficiency of biological systems. The use of CDP-based algorithms embedded in second-generation artificial intelligence platforms is described. In summary, noise is inherent to complex systems and has a functional role. The CDP provides the option of using noise to improve functionality.

Uncertainty and information causality in opportunity-as-artefact driving entrepreneurial actions

Purpose

Entrepreneurs prioritise and act on purposeful endeavours instigated to actions by the visions of profits and benefits in the perceived opportunities. In the state of maximum entropy, with disorderliness and disequilibrium, entrepreneurs select the preferred pathway, through the profit-sensing mechanism, with the best probability of success to bet on. Therefore, this paper unpacks the forces at work in the mechanism to explain how entrepreneurs respond to opportunity and interpret the signals to coalesce into organised actions.

Design/methodology/approach

This research is primarily a conceptual paper on entrepreneurial action and the mechanism leading to that action. It refers to thermodynamic principles and biological cases to explain the forces at work using mostly analogical comparisons and similarities.

Findings

This paper aims to present an alternative theoretical scaffolding for entrepreneurship researchers to explore non-rational entrepreneurial behaviours and actions in uncertain, unstable and non-equilibrium environments, thereby creating new and competing hypotheses under the backdrop of adaptive evolution and thermodynamics phenomena.

Research limitations/implications

The discussion featuring instinctively and naturally forming responses cannot fully explain the real entrepreneurial action as there is an element of free will and choices that are not discussed. While strategic choice and free-will shape decisions, they are preceded first by the attraction of the gradients and the biased motion in the direction of profit-attractant.

Practical implications

There remain essential links and issues not addressed in this “natural science”, constituting life science and physical science, oriented entrepreneurship research and exploration. Conceptualising opportunity-as-artefact and entrepreneurship as design, significant incidences of entrepreneurial actions can be explained by the presence of gradients stimulating entrepreneurial actions.

Social implications

This viewpoint of information causality in opportunity-as-artefact casts a new look at the venerable question of what causes entrepreneurial actions. Shane and Venkataraman brought into focus this conversation, initiating the conceptual definition of opportunity. To have entrepreneurship, entrepreneurial opportunities must come first. Figuring the signals arising from these opportunities and cueing entrepreneurs to action is the main focus of this study.

Originality/value

Considering the “mechanism” at work and the thermodynamical forces at play, the entrepreneurial design process appears to hold considerable promise for future research development.

Order stability via Fröhlich condensation in bio, eco, and social systems: The quantum-like approach

Stability of social and behavioural order in biological, ecological, and social systems is modelled within the formalism of the Fröhlich condensation. The latter is a high temperature analogue of the Bose-Einstein condensation and stability is approached via intensive pumping of energy into a system interacting with a bath. We start with the review of this formalism considering nonequilibrium thermodynamic and quantum frameworks. Although Fröhlich applied this formalism to bio-systems and the physical energy flows (electromagnetic, chemical, vibrational), he pointed out on the possibility to apply it to wider class of systems. We realize this program by using quantum-like modelling in combination with the information approach to biological and social systems, by treating them as information processors and introducing the notion of social energy (with its versions, as, e.g., social and behavioural energy). This formalism is applied to modelling of social stability in the modern open society characterized by powerful flows of information and huge information reservoir based on internet, including the variety of social networks. Then, it is applied to modelling of coherent behaviour in herds and flocks with the illustrative example of wolf packs. The essence of the paper is extracting conditions for the Fröhlich condensation and reformulating them in the purely information framework.