Context: At present, we lack a common understanding of both the process of cognition in living organisms and the construction of knowledge in embodied, embedded cognizing agents in general, including future artifactual cognitive agents under development, such as cognitive robots and softbots. Purpose: This paper aims to show how the info-computational approach (IC) can reinforce constructivist ideas about the nature of cognition and knowledge and, conversely, how constructivist insights (such as that the process of cognition is the process of (...) life) can inspire new models of computing. Method: The info-computational constructive framework is presented for the modeling of cognitive processes in cognizing agents. Parallels are drawn with other constructivist approaches to cognition and knowledge generation. We describe how cognition as a process of life itself functions based on info-computation and how the process of knowledge generation proceeds through interactions with the environment and among agents. Results: Cognition and knowledge generation in a cognizing agent is understood as interaction with the world (potential information), which by processes of natural computation becomes actual information. That actual information after integration becomes knowledge for the agent. Heinz von Foerster is identified as a precursor of natural computing, in particular bio computing. Implications: IC provides a framework for unified study of cognition in living organisms (from the simplest ones, such as bacteria, to the most complex ones) as well as in artifactual cognitive systems. Constructivist content: It supports the constructivist view that knowledge is actively constructed by cognizing agents and shared in a process of social cognition. IC argues that this process can be modeled as info-computation. (shrink)

Three special issues of Entropy journal have been dedicated to the topics of “InformationProcessing and Embodied, Embedded, Enactive Cognition”. They addressed morphological computing, cognitive agency, and the evolution of cognition. The contributions show the diversity of views present in the research community on the topic of computation and its relation to cognition. This paper is an attempt to elucidate current debates on computation that are central to cognitive science. It is written in the form of a dialog between (...) two authors representing two opposed positions regarding the issue of what computation is and could be, and how it can be related to cognition. Given the different backgrounds of the two researchers, which span physics, philosophy of computing and information, cognitive science, and philosophy, we found the discussions in the form of Socratic dialogue appropriate for this multidisciplinary/cross-disciplinary conceptual analysis. We proceed as follows. First, the proponent (GDC) introduces the info-computational framework as a naturalistic model of embodied, embedded, and enacted cognition. Next, objections are raised by the critic (MM) from the point of view of the new mechanistic approach to explanation. Subsequently, the proponent and the critic provide their replies. The conclusion is that there is a fundamental role for computation, understood as information processing, in the understanding of embodied cognition. (shrink)

Cognitive science is considered to be the study of mind (consciousness and thought) and intelligence in humans. Under such definition variety of unsolved/unsolvable problems appear. This article argues for a broad understanding of cognition based on empirical results from i.a. natural sciences, self-organization, artificial intelligence and artificial life, network science and neuroscience, that apart from the high level mental activities in humans, includes sub-symbolic and sub-conscious processes, such as emotions, recognizes cognition in other living beings as well as extended (...) and distributed/social cognition. The new idea of cognition as complex multiscale phenomenon evolved in living organisms based on bodily structures that process information, linking cognitivists and EEEE (embodied, embedded, enactive, extended) cognition approaches with the idea of morphological computation (info-computational self-organisation) in cognizing agents, emerging in evolution through interactions of a (living/cognizing) agent with the environment. (shrink)

Alan Turing’s pioneering work on computability, and his ideas on morphological computing support Andrew Hodges’ view of Turing as a natural philosopher. Turing’s natural philosophy differs importantly from Galileo’s view that the book of nature is written in the language of mathematics (The Assayer, 1623). Computing is more than a language used to describe nature as computation produces real time physical behaviors. This article presents the framework of Natural info-computationalism as a contemporary natural philosophy that builds (...) on the legacy of Turing’s computationalism. The use of info-computational conceptualizations, models and tools makes possible for the first time in history modeling of complex self-organizing adaptive systems, including basic characteristics and functions of living systems, intelligence, and cognition. (shrink)

Some intriguing questions such as: What is reality for an agent? How does reality of a bacterium differ from a reality of a human brain? Do we need representation in order to understand reality? are still widely debated. Starting with the presentation of the computing nature as an info-computational framework, where information is defined as a structure, and computation as information processing, we address questions of evolution of increasingly complex living agents through interactions with the environment. In this (...) context, the concept of computation will be discussed and the sense in which computation is observer-relative. Using the results on morphological/ morphogenetic computation as information self-organization we argue that reality for an agent is a result of networked agent-based computation. Consciousness is a (computational) process of information integration that evolved in organisms with nervous system. We present an argument why pancomputationalism (computing nature) is a sound scientific strategy and why panpsychism is not. (shrink)

Open peer commentary on the article “Info-computational Constructivism and Cognition” by Gordana Dodig-Crnkovic. Upshot: The main problems with info-computationalism are: (1) Its basic concept of natural computing has neither been defined theoretically or implemented practically. (2. It cannot encompass human concepts of subjective experience and intersubjective meaningful communication, which prevents it from being genuinely transdisciplinary. (3) Philosophically, it does not sufficiently accept the deep ontological differences between various paradigms such as von Foerster’s second- order cybernetics and Maturana (...) and Varela’s theory of autopoiesis, which are both erroneously taken to support info-computationalism. (shrink)

This paper presents a theoretical study of the binary oppositions underlying the mechanisms of natural computation understood as dynamical processes on natural information morphologies. Of special interest are the oppositions of discrete vs. continuous, structure vs. process, and differentiation vs. integration. The framework used is that of computing nature, where all natural processes at different levels of organisation are computations over informational structures. The interactions at different levels of granularity/organisation in nature, and the character of the phenomena that unfold (...) through those interactions, are modeled from the perspective of an observing agent. This brings us to the movement from binary oppositions to dynamic networks built upon mutually related binary oppositions, where each node has several properties. (shrink)

Open peer commentary on the article “Info-computational Constructivism and Cognition” by Gordana Dodig-Crnkovic. Upshot: I propose a mathematical approach to the framework developed in Dodig-Crnkovic’s target article. It points to an important property of natural computation, called the multiplicity principle (MP), which allows the development of increasingly complex cognitive processes and knowledge. While local dynamics are classically computable, a consequence of the MP is that the global dynamics is not, thus raising the problem of developing more elaborate computations, perhaps (...) with the help of Turing oracles. (shrink)

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial (deep learning, robotics), natural sciences (neuroscience, cognitive science, biology), and philosophy (philosophy of computing, philosophy of mind, natural philosophy). The question is, what (...) at this stage of the development the inspiration from nature, specifically its computational models such as info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach human-level intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial, natural sciences, and philosophy. The question is, what at this stage of the development the inspiration from nature, specifically its computational models such as (...) info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach humanlevel intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

Upshot: The variety of commentaries has shown that IC impacts on many disciplines, from physics to biology, to cognitive science, to ethics. Given its young age, IC still needs to fill in many gaps, some of which were pointed out by the commentators. My goal is both to illuminate some general topics of info-computationalism, and to answer specific questions in that context.

What is reality for an agent? What is minimal cognition? How does the morphology of a cognitive agent affect cognition? These are still open questions among scientists and philosophers. In this chapter we propose the idea of info-computational nature as a framework for answering those questions. Within the info-computational framework, information is defined as a structure, and computation as the dynamics of information. To an agent, nature therefore appears as an informational structure with computational dynamics. Both information and (...) computation in this context have broader meaning than in everyday use, and both are necessarily grounded in physical implementation. Evolution of increasingly complex living agents is understood as a process of morphological computation driven by agents’ interactions with the environment. It is a process much more complex than random variation; instead the mechanisms of change are morphological computational processes of self-organisation. Reality for an agent emerges as a result of interactions with the environment together with internal information processing. Following Maturana and Varela, we take cognition to be the process of living of an organism, and thus it appears on different levels of complexity, from cellular via organismic to social. The simpler the agent, the simpler its “reality” defined by the network of networks of info-computational processes, which constitute its cognition. The debated topic of consciousness takes its natural place in this framework, as a process of information integration that we suggest naturally evolved in organisms with a nervous system. Computing nature/pancomputationalism is sometimes confused with panpsychism or claimed to necessarily imply panpsychism, which we show is not the case. Even though we focus on natural systems in this chapter, the info-computational approach is general and can be used to model both biological and artifactual cognitive agents. (shrink)

In discussions regarding models of cognition, the very mention of “computationalism” often incites reactions against the insufficiency of the Turing machine model, its abstractness, determinism, the lack of naturalist foundations, triviality and the absence of clarity. None of those objections, however, concerns models based on natural computation or computing nature, where the model of computation is broader than symbol manipulation or conventional models of computation. Computing nature consists of physical structures that form layered computational architecture, with computation processes (...) ranging from quantum to chemical, biological/cognitive and social-level computation. It is argued that, on the lower levels of information processing in the brain, finite automata or Turing machines may still be adequate models, while, on the higher levels of whole-brain information processing, natural computing models are necessary. A layered computational architecture of the mind based on the intrinsic computing of physical systems avoids objections against early versions of computationalism in the form of abstract symbols manipulation. (shrink)

Open peer commentary on the article “Info-computational Constructivism and Cognition” by Gordana Dodig-Crnkovic. Upshot: Focusing on the relationship between info-computationalism and constructivism, I point out that there is a need to clarify fundamental concepts such as information, informational structures, and computation that obscure the theses regarding the relationship with constructivist thought. In particular, I wonder how we can reconcile constructivism with the view that all nature is a computational process.

Both Cybersemiotics and Info-computationalist research programmes represent attempts to unify understanding of information, knowledge and communication. The first one takes into account phenomenological aspects of signification which are insisting on the human experience "from within". The second adopts solely the view "from the outside" based on scientific practice, with an observing agent generating inter-subjective knowledge in a research community. The process of knowledge production, embodied into networks of cognizing agents interacting with the environment and developing through evolution is studied (...) on different levels of abstraction in both frames of reference. In order to develop scientifically tractable models of evolution of intelligence in informational structures from pre-biotic/chemical to living networked intelligent organisms, including the implementation of those models in artificial agents, a basic level language of Info-Computationalism has shown to be suitable. There are however contexts in which we deal with complex informational structures essentially dependent on human first person knowledge where high level language such as Cybersemiotics is the appropriate tool for conceptualization and communication. Two research projects are presented in order to exemplify the interplay of info-computational and higher-order approaches: The Blue Brain Project where the brain is modeled as info-computational system, a simulation in silico of a biological brain function, and Biosemiotics research on genes, information, and semiosis in which the process of semiosis is understood in info-computational terms. The article analyzes differences and convergences of Cybersemiotics and Info-computationalist approaches which by placing focus on distinct levels of organization, help elucidate processes of knowledge production in intelligent agents. (shrink)

Information is a basic structure of the world, while computation is a process of the dynamic change of information. This book provides a cutting-edge view of world's leading authorities in fields where information and computation play a central role. It sketches the contours of the future landscape for the development of our understanding of information and computation, their mutual relationship and the role in cognition, informatics, biology, artificial intelligence, and information technology. -/- This book is an utterly enjoyable and engaging (...) read which gives readers an opportunity to understand and relate phenomena seemingly unrelated in a completely new light — especially the connections between information, computation, cognition and life. -/- Contents: Cybersemiotics and the Question of Knowledge (Søren Brier) Information Dynamics in a Categorical Setting (Mark Burgin) Mathematics as a Biological Process (G J Chaitin) Information, Causation and Computation (John Collier) From Descartes to Turing: The Computational Content of Supervenience (S Barry Cooper) A Dialogue Concerning Two World Systems: Info-Computational vs Mechanistic (Gordana Dodig-Crnkovic & Vincent C Müller) Does Computing Embrace Self-Organization? (Wolfgang Hofkirchner) Analysis of Information and Computation in Physics Explains Cognitive Paradigms: From Full Cognition to Laplace Determinism to Statistical Determinism to Modern Approach (Vladik Kreinovich, Roberto Araiza & Juan Ferret) Bodies — Both Informed and Transformed Embodied Computation and Information Processing (Bruce J MacLennan) Computation on Information, Meaning and Representations: An Evolutionary Approach (Christophe Menant) Interior Grounding, Reflection, and Self-Consciousness (Marvin Minsky) A Molecular Dynamic Network: Minimal Properties and Evolutionary Implications (Walter Riofrio) Super-recursive Features of Evolutionary Processes and the Models for Computational Evolution (Darko Roglic) Towards a Modeling View of Computing (Oron Shagrir) What's Information, for an Organism or Intelligent Machine? How can a Machine or Organism Mean? (Aaron Sloman) Inconsistent Knowledge as a Natural Phenomenon: The Ranking of Reasonable Inferences as a Computational Approach to Naturally Inconsistent (Legal) Theories (Kees (CNJ) de Vey Mestdagh & Jaap Henk (JH) Hoepman) On the Algorithmic Nature of the World (Hector Zenil & Jean-Paul Delahaye) . (shrink)

Open peer commentary on the article “Info-computational Constructivism and Cognition” by Gordana Dodig-Crnkovic. Upshot: The limitations of materialism for studying cognition have motivated alternative epistemologies based on information and computation. I argue that these alternatives are also inherently limited and that these limits can only be overcome by considering materialism, info-computationalism, and cognition at the same time.

The contribution of the body to cognition and control in natural and artificial agents is increasingly described as “off-loading computation from the brain to the body”, where the body is said to perform “morphological computation”. Our investigation of four characteristic cases of morphological computation in animals and robots shows that the ‘off-loading’ perspective is misleading. Actually, the contribution of body morphology to cognition and control is rarely computational, in any useful sense of the word. We thus distinguish (1) (...) morphology that facilitates control, (2) morphology that facilitates perception and the rare cases of (3) morphological computation proper, such as ‘reservoir computing.’ where the body is actually used for computation. This result contributes to the understanding of the relation between embodiment and computation: The question for robot design and cognitive science is not whether computation is offloaded to the body, but to what extent the body facilitates cognition and control – how it contributes to the overall ‘orchestration’ of intelligent behaviour. (shrink)

Context: In previous papers, I suggested six rules proposed by Varela, Maturana and Uribe as a validation test to assess the autopoietic nature of a complex dynamic system. Identifying possible non-biological autopoietic systems is harder than merely assessing self-organization, existence of embodied boundaries and some observable autonomous behavioural capabilities: any rigorous assessment should include a close observation of the “intra-boundaries” phenomenology in terms of components’ self-production, their spatial distribution and the temporal occurrence of interaction events. Problem: Under which (...) physical and components’ relational conditions can some social systems be properly considered as autopoietic unities compliant with the six rules? Results: Dynamic systems can be classified according to “degrees of autonomous behaviour” that they may acquire as a result of the emergence of organizational closure (i.e., autonomy. Also, the different “degrees of attainable systemic autonomy” depend on the “degrees of autonomy” shown by a system’s dynamic components. For human social systems, a necessary balance between individuals’ autonomy and the heteronomous behaviour brought about on people by social norms (laws, culture, tradition or coercion) sets limits to the “degree of systemic autonomy” that human organizations may acquire. Therefore social systems, defined as dynamic systems composed of physical agents, could not attain the high “levels of systemic autonomy” ascribable to autopoietic systems without constraining the autonomy of agents to “levels” that are incompatible with spontaneous human behaviour. Also, social organizations seen as composed of physical agents interacting in physical space cannot be construed as autopoietic systems. Alternatively, if seen as composed of “process-like” entities, where agents participate as actors within processes, some social systems could be described as autopoietic wholes existing in the abstract space in which we distinguish interactions between processes, provided that we can assess compliance with the rules for some specific cases. Implications: These conclusions contribute to the debate on the possible autopoietic nature of some human social systems and to grasping the opportunity to shift focus to the more interesting issue of the “degrees of systemic autonomy” that human organizations could acquire (if needed) without imposing unbearable limitations on the autonomy of human actors. Also, the conceptual framework of this explanatory approach could be used in practical terms to assist the development of new dynamic modelling languages capable of simulating social systems. (shrink)

The book presents investigations into the world of info-computational nature, in which information constitutes the structure, while computational process amounts to its change. Information and computation are inextricably bound: There is no computation without informational structure, and there is no information without computational process. Those two complementary ideas are used to build a conceptual net, which according to Novalis is a theoretical way of capturing reality. We apprehend the reality within a framework known as natural computationalism, the view that (...) the whole universe can be understood as a computational system at many different levels - from quantum mechanical world, to biological organisms including intelligent minds and their societies. Questions about nature of information and computation and their unified view are addressed along with application of info- computational approach to knowledge generation. (shrink)

It is usual when writing on research methodology in dissertations and thesis work within Software Engineering to refer to Empirical Methods, Grounded Theory and Action Research. Analysis of Constructive Research Methods which are fundamental for all knowledge production and especially for concept formation, modeling and the use of artifacts is seldom given, so the relevant first-hand knowledge is missing. This article argues for introducing of the analysis of Constructive Research Methods, as crucial for understanding of research process and knowledge production. (...) The paper provides characterization of the Constructive Research Method and its relations to Action Research and Grounded Theory. Illustrative example of Blue Brain Project is presented. Finally, foundations of Constructive Research are analyzed within the framework of Info-Computationalism which provides models of knowledge construction by information processing in a cognizing agent. (shrink)

This article addresses the question of the mechanisms of the emergence of structure and meaning in the biological and physical sciences. It proceeds from an examination of the concept of intentionality and proposes a model of intentional behavior on the basis of results of computer simulations of structural and functional self-organization. Current attempts to endow intuitive aspects of meaningful complexity with operational content are analyzed and the metaphor of DNA as a computer program (the `genetic program') is critically examined (...) in relation to an alternative metaphor of DNA as data. It is argued that relatively simple networks of boolean automata can classify and recognize patterns of binary strings on the basis of non-programmed, self-generated criteria, but lack a capacity for self-observation and interpretation. To overcome this problem it is necessary to clarify the relationships between the goals and underlying mechanisms of a process and between a system and its environment. It will be shown that memory devices that record the histories of interactions are essential for models of conscious and unconscious intentional behavior and that the possibility of infinitely sophisticated - and therefore unprogrammable - machines cannot be avoided. It will be argued that the notion of infinite sophistication allows the ideas of self-organization and physical determinism to be reconciled. These models will be used to suggest how the voluntary aspect of decision-making in general can emerge out of functional self-organizing processes. The conclusion will introduce the notion of `underdetermination' of theories, which imposes an intrinsic limitation on models of complex natural systems - a limitation that, at the same time, may be precisely what makes possible mutual understanding and intersubjectivity. (shrink)

All epistemic agents physically consist of parts that must somehow comprise an integrated cognitive self. Biological individuals consist of subunits (organs, cells, molecular networks) that are themselves complex and competent in their own context. How do coherent biological Individuals result from the activity of smaller sub-agents? To understand the evolution and function of metazoan 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 paper 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 - suggests 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 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. (shrink)

Open peer commentary on the article “Exploration of the Functional Properties of Interaction: Computer Models and Pointers for Theory” by Etienne B. Roesch, Matthew Spencer, Slawomir J. Nasuto, Thomas Tanay & J. Mark Bishop. Upshot: Artificial life computer simulations hold the potential for demonstrating the kinds of bottom-up, cooperative, self-organizing processes that underlie the self-construction of observer-actors. This is a worthwhile, if limited, attempt to use such simulations to address this set of core constructivist concerns. Although we concur (...) with much of the philosophical perspective in the target article, we take issue with some of the implied positions related to dynamical systems, sensorimotor contingency theory, and neural information processing. Ideally, we would like to see computational approaches more directly address adaptive, constructive processes and mechanisms operant in minds and brains. This would entail using tasks that are more relevant to the psychology of human and animal learning than performing digit sums or sorts. It also could involve relating the dynamics of agents more explicitly to ensembles of communicating neural assemblies. (shrink)

Recent developments in computer science, particularly ”data-driven procedures“ have opened a new level of design and engineering. This has also affected architecture. The publication collects contributions on Coding as Literacy by computer scientists, mathematicians, philosophers, cultural theorists, and architects. The main focus in the book is the observation of computer-based methods that go beyond strictly case-based or problem-solution-oriented paradigms. This invites readers to understand Computational Procedures as being embedded in an overarching ”media literacy“ that can be revealed through, and acquired (...) by, ”computational literacy“, and to consider the data processed in the above-mentioned methods as being beneficial in terms of quantum physics. ”Self-Organizing Maps“ (SOM), which were first introduced over 30 years ago, will serve as the concrete reference point for all further discussions. (shrink)

In this thesis, I discuss the organism's self-organization from the perspective of relational ontology. I critically examine scientific and philosophical sources that appeal to the concept of self-organization. By doing this, I aim to carry out a thorough investigation into the underlying reasons of emergent order within the ontogeny of the organism. Moreover, I focus on the relation between universal dynamics of organization and the organization of living systems. I provide a historical review of the development of modern (...) ideas related to self-organization. These ideas have been developed in relation to various research areas including thermodynamics, molecular biology, developmental biology, systems theory, and so on. In order to develop a systematic understanding of the concept, I propose a conceptual distinction between transitional self-organization and regulative self-organization. The former refers to the spontaneous emergence of order, whereas the latter refers to the self-maintaining characteristic of the living systems. I show the relation between these two types of organization within biological processes. I offer a critical analysis of various theories within the organizational approach. Several ideas and notions in these theories originate from the early studies in cybernetics. More recently, autopoiesis and the theory of biological autonomy asserted certain claims that were critical toward the ideas related to self-organization. I advocate a general theory of self-organization against these criticisms. I also examine the hierarchical nature of the organism's organization, as this is essential to understand regulative self-organization. I consider the reciprocal relation between bottom-up and top-down dynamics of organization as the basis of the organism's individuation. To prove this idea, I appeal to biological research on molecular self-assembly, pattern formation (including reaction-diffusion systems), and the self-organized characteristic of the immune system. Finally, I promote the idea of diachronic emergence by drawing support from biological self-organization. I discuss the ideas related to constraints, potentiality, and dynamic form in an attempt to reveal the emergent nature of the organism. To demonstrate the dynamicity of form, I examine research into biological oscillators. I draw the following conclusions: synchronic condition of the organism is irreducibly processual and relational, and this is the basis of the organism's potentiality for various organizational states. (shrink)

Open peer commentary on the article “Info-computational Constructivism and Cognition” by Gordana Dodig-Crnkovic. Upshot: Dodig-Crnkovic’s “info-computational constructivism” (IC), as an essential part of a constructivist approach, needs integration with the logical, mathematical and physical evidence coming from quantum field theory (QFT) as the fundamental physics of the emergence of “complex systems” in all realms of natural sciences.

In _Selving: A Relational Theory of Self Organization_, Irene Fast invokes the basic distinction between the self as "me" and the self as "I" in order to develop a contemporary theory of the self as subject. In a return to Freud's clinical finding that all psychological processes are personally motivated, she elaborates a notion of the "I-self" that is intrinsically dynamic and relational. Within this conception, our perceiving, thinking, feeling, and acting are not what our (...) self does; rather, they are what our self is. According to Fast, the basic unit of the dynamic I-self --of selving --is a scheme of personally motivated interaction between self and nonself. This notion, which comprehends development as a product of integration and differentiation among discrete I-schemes, provides a radically new framework for understanding those dynamic phenomena that Freud included within his structural model of the mind and that contemporary theorists have addressed within object relational perspectives. Via the notion of selving, Fast likewise brings fresh insight to a host of issues that have engaged psychoanalysts and developmental psychologists in recent years. These topics include the place of bodily experience in a relational model of mind, the organization of self as simultaneously individual and relational, the formulation of a constructivist model of psychic structure, among others. _Selving_ is not only a lucid demonstration of how a relational theory of self can reorder clinical observations in conceptually and therapeutically illuminating ways. It is also a convincing demonstration of how a constructivist model emphasizing the interactive nature of meaning-making provides bridges to Piagetian theory, developmental research, and observational infancy studies. (shrink)

All information results from a process, intrinsic to living beings, of info-autopoiesis or information self-production; a sensory commensurable, self-referential feedback process immanent to Bateson’s ‘difference which makes a difference’. To highlight and illustrate the fundamental nature of the info-autopoietic process, initially, two simulations based on one-parameter feedback are presented. The first, simulates a homeostatic control mechanism (thermostat) which is representative of a mechanistic, cybernetic system with very predictable dynamics, fully dependent on an external referent. The (...) second, simulates a homeorhetic process, inherent to biological systems, illustrating a self-referenced, autonomous system. Further, the active incorporation/interference of viral particles by prokaryotic cells and the activation of CRISPR-Cas can be understood as info-autopoiesis at the most fundamental cellular level, as well as constituting a planetary network of self-referenced information. Moreover, other examples of the info-autopoietic nature of information are presented to show the generality of its applicability. In short, info-autopoiesis is a recursive process that is sufficiently generic to be the only basis for information in nature: from the single cell, to multi-cellular organisms, to consideration of all types of natural and non-natural phenomena, including tools and artificial constructions. (shrink)

Predictive processing approaches to the mind are increasingly popular in the cognitive sciences. This surge of interest is accompanied by a proliferation of philosophical arguments, which seek to either extend or oppose various aspects of the emerging framework. In particular, the question of how to position predictive processing with respect to enactive and embodied cognition has become a topic of intense debate. While these arguments are certainly of valuable scientific and philosophical merit, they risk underestimating the variety of approaches gathered (...) under the predictive label. Here, we first present a basic review of neuroscientific, cognitive, and philosophical approaches to PP, to illustrate how these range from solidly cognitivist applications—with a firm commitment to modular, internalistic mental representation—to more moderate views emphasizing the importance of ‘body-representations’, and finally to those which fit comfortably with radically enactive, embodied, and dynamic theories of mind. Any nascent predictive processing theory must take into account this continuum of views, and associated theoretical commitments. As a final point, we illustrate how the Free Energy Principle attempts to dissolve tension between internalist and externalist accounts of cognition, by providing a formal synthetic account of how internal ‘representations’ arise from autopoietic self-organization. The FEP thus furnishes empirically productive process theories by which to guide discovery through the formal modelling of the embodied mind. (shrink)

'Self organization' is a popular theme in current studies of human social activity, enterprises, and information technology (IT). This document introduces one well developed theory of self organization (autopoietic theory) and discusses its application to enterprises and their management.

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial, natural sciences, and philosophy. The question is, what at this stage of the development the inspiration from nature, specifically its computational models such as (...) info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach humanlevel intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

Computers today are not only the calculation tools - they are directly (inter)acting in the physical world which itself may be conceived of as the universal computer (Zuse, Fredkin, Wolfram, Chaitin, Lloyd). In expanding its domains from abstract logical symbol manipulation to physical embedded and networked devices, computing goes beyond Church-Turing limit (Copeland, Siegelman, Burgin, Schachter). Computational processes are distributed, reactive, interactive, agent-based and concurrent. The main criterion of success of computation is not its termination, but the adequacy of (...) its response, its speed, generality and flexibility; adaptability, and tolerance to noise, error,faults, and damage. Interactive computing is a generalization of Turing computing, and it calls for new conceptualizations (Goldin, Wegner). In the info-computationalist framework, with computation seen as information processing, natural computation appears as the most suitable paradigm of computation and information semantics requires logical pluralism. (shrink)

The Darwinian concept of natural selection was conceived within a set of Newtonian background assumptions about systems dynamics. Mendelian genetics at first did not sit well with the gradualist assumptions of the Darwinian theory. Eventually, however, Mendelism and Darwinism were fused by reformulating natural selection in statistical terms. This reflected a shift to a more probabilistic set of background assumptions based upon Boltzmannian systems dynamics. Recent developments in molecular genetics and paleontology have put pressure on Darwinism once again. Current work (...) on self-organizing systems may provide a stimulus not only for increased problem solving within the Darwinian tradition, especially with respect to origins of life, developmental genetics, phylogenetic pattern, and energy-flow ecology, but for deeper understanding of the very phenomenon of natural selection itself. Since self-organizational phenomena depend deeply on stochastic processes, self-organizational systems dynamics advance the probability revolution. In our view, natural selection is an emergent phenomenon of physical and chemical selection. These developments suggest that natural selection may be grounded in physical law more deeply than is allowed by advocates of the autonomy of biology, while still making it possible to deny, with autonomists, that evolutionary explanations can be modeled in terms of a deductive relationship between laws and cases. We explore the relationship between, chance, self-organization, and selection as sources of order in biological systems in order to make these points. (shrink)

Eco-cognitive computationalism considers computation in context, following some of the main tenets advanced by the recent cognitive science views on embodied, situated, and distributed cognition. It is in the framework of this eco-cognitive perspective that we can usefully analyze the recent attention in computer science devoted to the importance of the simplification of cognitive and motor tasks caused in organic entities by the morphological features: ignorant bodies can be domesticated to become useful “mimetic bodies”, that is able to render (...) an intertwined computation simpler, resorting to that “simplexity” of animal embodied cognition, which represents one of the main quality of organic agents. Through eco-cognitive computationalism we can clearly acknowledge that the concept of computation changes, depending on historical and contextual causes, and we can build an epistemological view that illustrates the “emergence” of new kinds of computations, such as the one regarding morphological computation. This new perspective shows how the computational domestication of ignorant entities can originate new unconventional cognitive embodiments. In the last part of the article I will introduce the concept of overcomputationalism, showing that my proposed framework helps us see the related concepts of pancognitivism, paniformationalism, and pancomputationalism in a more naturalized and prudent perspective, avoiding the excess of old-fashioned ontological or metaphysical overstatements. (shrink)

Demonstration of illusiveness of basic beliefs of the Modern Synthesis implies the existence of evolutionary mechanisms that do not require natural selection for the origin of adaptations. This requires adaptive changes that occur independently from replication, but can occasionally become heritable. Plastic self-organizational changes regulated by genome are largely incorporable into the old theory. A fundamentally different source of adaptability is semiosis which includes the agent’s free choice. Adding semiosis into the theory of Extended Evolutionary Synthesis completes the distancing (...) from the Modern Synthesis. I focus here on the importance of semiosis as the necessary factor in organisms’ meaning making. (shrink)

This paper connects information with computation and cognition via concept of agents that appear at variety of levels of organization of physical/chemical/cognitive systems – from elementary particles to atoms, molecules, life-like chemical systems, to cognitive systems starting with living cells, up to organisms and ecologies. In order to obtain this generalized framework, concepts of information, computation and cognition are generalized. In this framework, nature can be seen as informational structure with computational dynamics, where an (info-computational) agent is needed for (...) the potential information of the world to actualize. Starting from the definition of information as the difference in one physical system that makes a difference in another physical system – which combines Bateson and Hewitt’s definitions, the argument is advanced for natural computation as a computational model of the dynamics of the physical world, where information processing is constantly going on, on a variety of levels of organization. This setting helps us to elucidate the relationships between computation, information, agency and cognition, within the common conceptual framework, with special relevance for biology and robotics. (shrink)

In this paper I link two hitherto disconnected sets of results in the philosophy of emotions and explore their implications for the computational theory of mind. The argument of the paper is that, for just the same reasons that some computationalists have thought that cognition may be a natural kind, so the same can plausibly be argued of emotion. The core of the argument is that emotions are a representation-governed phenomenon and that the explanation of how they figure in behaviour (...) must as such be undertaken in those terms. I conclude with some interdisciplinary reflections in defence of the hypothesis that emotions might be more fundamental in the organization of behaviour than cognition; that, in effect, we may be emoters before we are cognizers . The aim of the paper is: (1) to introduce a number of promising results in philosophical and empirical emotion theory to a wider audience; and (2) to begin the task of organizing those results into a computational theoretical framework. (shrink)

As computational systems burgeon with advancing artificial intelligence (AI), the deterministic frameworks underlying them face novel challenges, especially when interfacing with self-modifying code. The Executioner Paradox, introduced herein, exemplifies such a challenge where a deterministic Executioner Machine (EM) grapples with self-aware and self-modifying code. This unveils a self-referential dilemma, highlighting a gap in current deterministic computational frameworks when faced with self-evolving code. In this article, the Executioner Paradox is proposed, highlighting the nuanced interactions between deterministic (...) decision-making and self-aware code, and the ensuing challenges. This article advocates for a re-evaluation of existing deterministic frameworks, emphasizing the need for adaptive decision-making mechanisms in computational systems. By dissecting the Executioner Paradox, the aim is to foster a robust discussion on evolving deterministic frameworks to accommodate the dynamic nature of self-modifying code, thereby contributing a forward-looking lens to the discourse on computational systems amidst advancing AI. (shrink)

Natural language syntax yields an unbounded array of hierarchically structured expressions. We claim that these are used in the service of active inference in accord with the free-energy principle (FEP). While conceptual advances alongside modelling and simulation work have attempted to connect speech segmentation and linguistic communication with the FEP, we extend this program to the underlying computations responsible for generating syntactic objects. We argue that recently proposed principles of economy in language design—such as “minimal search” criteria from theoretical syntax—adhere (...) to the FEP. This affords a greater degree of explanatory power to the FEP—with respect to higher language functions—and offers linguistics a grounding in first principles with respect to computability. While we mostly focus on building new principled conceptual relations between syntax and the FEP, we also show through a sample of preliminary examples how both tree-geometric depth and a Kolmogorov complexity estimate (recruiting a Lempel–Ziv compression algorithm) can be used to accurately predict legal operations on syntactic workspaces, directly in line with formulations of variational free energy minimization. This is used to motivate a general principle of language design that we term Turing–Chomsky Compression (TCC). We use TCC to align concerns of linguists with the normative account of self-organization furnished by the FEP, by marshalling evidence from theoretical linguistics and psycholinguistics to ground core principles of efficient syntactic computation within active inference. (shrink)

Our aim in this article is to attempt to discuss propagating organization of process, a poorly articulated union of matter, energy, work, constraints and that vexed concept, “information”, which unite in far from equilibrium living physical systems. Our hope is to stimulate discussions by philosophers of biology and biologists to further clarify the concepts we discuss here. We place our discussion in the broad context of a “general biology”, properties that might well be found in life anywhere in the cosmos, (...) freed from the specific examples of terrestrial life after 3.8 billion years of evolution. By placing the discussion in this wider, if still hypothetical, context, we also try to place in context some of the extant discussion of information as intimately related to DNA, RNA and protein transcription and translation processes. While characteristic of current terrestrial life, there are no compelling grounds to suppose the same mechanisms would be involved in any life form able to evolve by heritable variation and natural selection. In turn, this allows us to discuss at least briefly, the focus of much of the philosophy of biology on population genetics, which, of course, assumes DNA, RNA, proteins, and other features of terrestrial life. Presumably, evolution by natural selection—and perhaps self-organization—could occur on many worlds via different causal mechanisms. Here we seek a non-reductionist explanation for the synthesis, accumulation, and propagation of information, work, and constraint, which we hope will provide some insight into both the biotic and abiotic universe, in terms of both molecular self reproduction and the basic work energy cycle where work is the constrained release of energy into a few degrees of freedom. The typical requirement for work itself is to construct those very constraints on the release of energy that then constitute further work. Information creation, we argue, arises in two ways: first information as natural selection assembling the very constraints on the release of energy that then constitutes work and the propagation of organization. Second, information in a more extended sense is “semiotic”, that is about the world or internal state of the organism and requires appropriate response. The idea is to combine ideas from biology, physics, and computer science, to formulate explanatory hypotheses on how information can be captured and rendered in the expected physical manifestation, which can then participate in the propagation of the organization of process in the expected biological work cycles to create the diversity in our observable biosphere. Our conclusions, to date, of this enquiry suggest a foundation which views information as the construction of constraints, which, in their physical manifestation, partially underlie the processes of evolution to dynamically determine the fitness of organisms within the context of a biotic universe. (shrink)

A working hypothesis of computationalism is that Mind arises, not from the intrinsic nature of the causal properties of particular forms of matter, but from the organization of matter. If this hypothesis is correct, then a wide range of physical systems (e.g. optical, chemical, various hybrids, etc.) should support Mind, especially computers, since they have the capability to create/manipulate organizations of bits of arbitrarily complexity and dynamics. In any particular computer, these bit patterns are quite physical, but their particular physicality (...) is considered irrelevant (since they could be replaced by other physical substrata). (shrink)

Purpose. The purpose is to prove the synchronicity of anthropogenesis, noogenesis and sociogenesis based on emotions, which are their self-organizational principles, as well as to reveal the synergistic essence of these processes. Theoretical basis. The study is based on the self-organizational paradigm, the theory of autopoiesis, labour theory, pananthropological concept, as well as on the concept of synergy of biological and mental phenomena. Originality. The concept of synchronicity of anthropogenesis, noogenesis and sociogenesis based on the emotions is (...) substantiated. The concept of self-organizational emergence of emotions on the basis of hormones is developed. It is established that anthropogenesis is a process of anthropologisation of life based on biochemical reactions in the form of hormones and emotions, which are a synergy of genetic information, biochemical processes, instincts, and physiological phenomena. It was outlined that noogenesis has an emotional dimension, because emotions are the basis for self-organization of rationality, which begins at the level of emotional consciousness. The author shows the specifics of sociogenesis, which self-organizes based on social emotions, which in their turn "distinguish" a man from the sphere of natural existence based on the ability to control emotions. Conclusions. Emotions arise self-organizationally on the basis of hormones. They are self-organizational factors of anthropogenesis, noogenesis and sociogenesis based on the synergistic effect that arises through the combination of emotions and hormones at the biochemical level. The basic principle of anthropology is emotions that synchronize anthropogenesis, noogenesis and sociogenesis, which manifests themselves on the physical, mental, and spiritual levels. At the bodily level, emotions are expressed as biochemical and hormonal reactions. At the spiritual level emotions create the basis for the development of the mind, which originates as emotional consciousness. Emotions self-organize the process of anthropologisation of life, which is possible based on the synergy of human genome, biochemical, physiological phenomena and instincts. The concepts of synchronicity of anthropogenesis, noogenesis and sociogenesis and self-organizational emergence of emotions based on hormones initiate a promising direction of further research of the role of emotions in the processes of self-organization of social phenomena. (shrink)

This article addresses the issue of objectivism vs constructivism in two areas,biology and cognitive science, which areintermediate between the natural sciences suchas physics (where objectivism is dominant) andthe human and social sciences (whereconstructivism is widespread). The issues inbiology and in cognitive science are intimatelyrelated; in each of these twin areas, the objectivism vs constructivism issue isinterestingly and rather evenly balanced; as aresult, this issue engenders two contrastingparadigms, each of which has substantialspecific scientific content. The neo-Darwinianparadigm in biology is closely resonant (...) withthe classical cognitivist paradigm in cognitivescience, and both of them are intrinsicallyobjectivist. The organismic paradigm inbiology, based on the concept of autopoiesis,is consonant with the paradigm of enaction incognitive science; the latter paradigms are bothprofoundly constructivist.In cognitive science, the objectivism vsconstructivism issue is internal to thescientific field itself and reflexivity isinescapable. At this level, strong ontologicalobjectivism is self-contradictory and thereforeuntenable. Radical constructivism isself-coherent; but it also rehabilitatesa weak form of objectivism as a pragmaticallyviable alternative. In conclusion, there is aneven-handed reciprocity between objectivistand constructivist perspectives. Finally, thearticle examines the consequences of thisconclusion for fields other than cognitivescience: biology; physics and the naturalsciences; and the human and social sciences. (shrink)

This paper connects information with computation and cognition via concept of agents that appear at variety of levels of organization of physical/chemical/cognitive systems – from elementary particles to atoms, molecules, life-like chemical systems, to cognitive systems starting with living cells, up to organisms and ecologies. In order to obtain this generalized framework, concepts of information, computation and cognition are generalized. In this framework, nature can be seen as informational structure with computational dynamics, where an (info-computational) agent is needed for (...) the potential information of the world to actualize. Starting from the definition of information as the difference in one physical system that makes a difference in another physical system – which combines Bateson and Hewitt’s definitions, the argument is advanced for natural computation as a computational model of the dynamics of the physical world, where information processing is constantly going on, on a variety of levels of organization. This setting helps us to elucidate the relationships between computation, information, agency and cognition, within the common conceptual framework, with special relevance for biology and robotics. (shrink)

Three arguments are given to show that neural constructivism lacks an essential ingredient to explain cognitive development. Based on results in the theory of adaptive signal analysis, adaptive biological pattern information and self-organization in nonlinear systems of information processing, it is concluded that neural constructivism should be further extended to accommodate the occurrence of phase transitions generating qualitative development in the sense of Piaget.

Context: Using radical constructivism, society can be considered from the perspective of asking the question, “Who conceives of society?” In Luhmann ’s social systems theory, this question itself is considered as a construct of the communication among reflexive agents. Problem: Structuration of expectations by codes operating in interhuman communications positions both communicators and communications in a multi-dimensional space in which their relations can be provided with meaning at the supra-individual level. The codes can be functionally different and symbolically generalized. Method: (...) More than Luhmann, I focus on the hypothetical status of the communication of meaning and the uncertainty involved. Meaning can be communicated because of reflexivity in interhuman communications; meaning cannot be observed. Results: The communication of denotations between semantic domains can generate “horizons of meaning” as reflexive orders that remain structurally coupled to individual minds. This elusive order contains a trade-off between “organization” at interfaces integrating expectations at each moment of time, and the potential of further differentiation among symbolically generalized codes of communication in a “self-organization” over time. Implications: One can model the coding in the communication of meaning as latent variables that evolve as an implication of the interacting intentions and expectations. The structure of expectations can be visualized and animated using semantic maps. The self-organizing horizons of meaning operate in a multidimensional space different from the network topology, and at another pace, since meaning is provided to events from the perspective of hindsight. Constructivist content: This perspective of the radical constructedness of social reality transforms the status of agency and organization in sociological theorizing from a source of change to a resource of communicative competencies and reflexive performativity. (shrink)

This chapter explains the notions of information, communication and learning in the context of the complex adaptive systems theory, under the version proposed by M. Gell‐Mann. Within the class of such systems, it focuses attention on complex and self‐organized natural systems as analyzed by H. Atlan. The chapter describes the epistemological context and the formal definition of self‐organization according to H. Atlan, because this definition results from a re‐interpretation of the Shannonian theorem of the noisy channel by applying (...) it to a system organized into several hierarchical levels. It is gradually restore Atlan's construction of the notion of the meaning of information in a hierarchical system, by contrasting the principles of order from noise and organizational noise and by accordingly distinguishing the concepts of complexity and complication. The principle of complexity from noise, which lies at the heart of the concept of self‐organization proposed by H. Atlan. (shrink)

Replying to the variegated responses by theologian Langdon Gilkey, philosophers Richard McClelland and Robert Deltete, and biologist Rudolf B. Brun, I emphasize three elements of my theological use of autopoietic theory: (1) Autopoietic systems are less than self‐constitutive, since they do not create themselves from scratch, but more than self‐organizing, since they are capable of producing new elements inside the local system. Correspondingly, the theological importance of autopoietic theory is not found within the doctrine of a creation out (...) of nothing but within the doctrine of non‐uniform continuous creation. (2) Locating the concept of autopoiesis within third‐generation systems theory, I underline the pluriform character of type‐different systems; the possibility of giving a full causal account from the purview of any privileged single systems (including physics) is thus denied. (3) I distinguish between two complementary roles of theology in the dialogue between science and religion: whereas theology1 offers a participatory second‐order description of the internal meaning of particular traditions of faith, theology2 provides a third‐order inquiry into the external coherence between religious and nonreligious worlds of meaning. Theology2, however, always presupposes the internal descriptions of theology1. On this basis, my use of autopoietic theory is related to the theologies of creation and providence of Paul Tillich and Langdon Gilkey; likewise, I discuss various theological strategies for relating a theology of creation to standard interpretations of evolution. (shrink)