In this paper, we set out to develop a theoretical and conceptual framework for the new field of Radical Embodied Cognitive Neuroscience. This framework should be able to integrate insights from several relevant disciplines: theory on embodied cognition, ecological psychology, phenomenology, dynamical systems theory, and neurodynamics. We suggest that the main task of Radical Embodied Cognitive Neuroscience is to investigate the phenomenon of skilled intentionality from the perspective of the self-organization of the brain-body-environment system, while doing justice to (...) the phenomenology of skilled action. In previous work, we have characterized skilled intentionality as the organism's tendency toward an optimal grip on multiple relevant affordances simultaneously. Affordances are possibilities for action provided by the environment. In the first part of this paper, we introduce the notion of skilled intentionality and the phenomenon of responsiveness to a field of relevant affordances. Second, we use Friston's work on neurodynamics, but embed a very minimal version of his Free Energy Principle in the ecological niche of the animal. Thus amended, this principle is helpful for understanding the embeddedness of neurodynamics within the dynamics of the system “brain-body-landscape of affordances.” Next, we show how we can use this adjusted principle to understand the neurodynamics of selective openness to the environment: interacting action-readiness patterns at multiple timescales contribute to the organism's selective openness to relevant affordances. In the final part of the paper, we emphasize the important role of metastable dynamics in both the brain and the brain-body-environment system for adequate affordance-responsiveness. We exemplify our integrative approach by presenting research on the impact of Deep Brain Stimulation on affordance responsiveness of OCD patients. (shrink)
Stuart Kauffman here presents a brilliant new paradigm for evolutionary biology, one that extends the basic concepts of Darwinian evolution to accommodate recent findings and perspectives from the fields of biology, physics, chemistry and mathematics. The book drives to the heart of the exciting debate on the origins of life and maintenance of order in complex biological systems. It focuses on the concept of self-organization: the spontaneous emergence of order that is widely observed throughout nature Kauffman argues that (...)self-organization plays an important role in the Darwinian process of natural selection. Yet until now no systematic effort has been made to incorporate the concept of self-organization into evolutionary theory. The construction requirements which permit complex systems to adapt are poorly understood, as is the extent to which selection itself can yield systems able to adapt more successfully. This book explores these themes. It shows how complex systems, contrary to expectations, can spontaneously exhibit stunning degrees of order, and how this order, in turn, is essential for understanding the emergence and development of life on Earth. Topics include the new biotechnology of applied molecular evolution, with its important implications for developing new drugs and vaccines; the balance between order and chaos observed in many naturally occurring systems; new insights concerning the predictive power of statistical mechanics in biology; and other major issues. Indeed, the approaches investigated here may prove to be the new center around which biological science itself will evolve. The work is written for all those interested in the cutting edge of research in the life sciences. (shrink)
We describe a “centipede’s dilemma” that faces the sciences of human interaction. Research on human interaction has been involved in extensive theoretical debate, although the vast majority of research tends to focus on a small set of human behaviors, cognitive processes, and interactive contexts. The problem is that naturalistic human interaction must integrate all of these factors simultaneously, and grander theoretical mitigation cannot come only from focused experimental or computational agendas. We look to dynamical systems theory as a framework for (...) thinking about how these multiple behaviors, processes, and contexts can be integrated into a broader account of human interaction. By introducing and utilizing basic concepts of self-organization and synergy, we review empirical work that shows how human interaction is flexible and adaptive and structures itself incrementally during unfolding interactive tasks, such as conversation, or more focused goal-based contexts. We end on acknowledging that dynamical systems accounts are very short on concrete models, and we briefly describe ways that theoretical frameworks could be integrated, rather than endlessly disputed, to achieve some success on the centipede’s dilemma of human interaction. (shrink)
Possibly the most fundamental scientific problem is the origin of time and causality. The inherent difficulty is that all scientific theories of origins and evolution consider the existence of time and causality as given. We tackle this problem by starting from the concept of self-organization, which is seen as the spontaneous emergence of order out of primordial chaos. Self-organization can be explained by the selective retention of invariant or consistent variations, implying a breaking of the initial (...) symmetry exhibited by randomness. In the case of time, we start from a random graph connecting primitive “events”. Selection on the basis of consistency eliminates cyclic parts of the graph, so that transitive closure can transform it into a partial order relation of precedence. Causality is assumed to be carried by causal “agents” which undergo a more traditional variation and selection, giving rise to causal laws that are partly contingent, partly necessary. (shrink)
Recent work on selforganization promises an explanation of complex order which is independent of adaptation. Self-organizing systems are complex systems of simple units, projecting order as a consequence of localized and generally nonlinear interactions between these units. Stuart Kauffman offers one variation on the theme of self-organization, offering what he calls a ``statistical mechanics'' for complex systems. This paper explores the explanatory strategies deployed in this ``statistical mechanics,'' initially focusing on the autonomy of statistical (...) explanation as it applies in evolutionary settings and then turning to Kauffman's analysis. Two primary morals emerge as a consequence of this examination: first, the view that adaptation and self-organization should be seen as competing theories or models is misleading and simplistic; and second, while we need a synthesis treating self-organization and adaptation as geared toward different problems, at different levels of organization, and deploying different methods, we do not yet have such a synthesis. (shrink)
A growing body of evidence in cognitive psychology and neuroscience suggests a deep interconnection between sensory-motor and language systems in the brain. Based on recent neurophysiological findings on the anatomo-functional organization of the fronto-parietal network, we present a computational model showing that language processing may have reused or co-developed organizing principles, functionality, and learning mechanisms typical of premotor circuit. The proposed model combines principles of Hebbian topological self-organization and prediction learning. Trained on sequences of either motor or (...) linguistic units, the network develops independent neuronal chains, formed by dedicated nodes encoding only context-specific stimuli. Moreover, neurons responding to the same stimulus or class of stimuli tend to cluster together to form topologically connected areas similar to those observed in the brain cortex. Simulations support a unitary explanatory framework reconciling neurophysiological motor data with established behavioral evidence on lexical acquisition, access, and recall. (shrink)
This thesis contributes to a better conceptual understanding of how self-organized control works. I begin by analyzing the control problem and its solution space. I argue that the two prominent solutions offered by classical cognitive science (centralized control with rich commands, e.g., the Fodorian central systems) and embodied cognitive science (distributed control with simple commands, such as the subsumption architecture by Rodney Brooks) are merely two positions in a two-dimensional solution space. I outline two alternative positions: one is distributed (...) control with rich commands, defended by proponents of massive modularity hypothesis; the other is centralized control with simple commands. My goal is to develop a hybrid account that combines aspects of the second alternative position and that of the embodied cognitive science (i.e., centralized and distributed controls with simple commands). Before developing my account, I discuss the virtues and challenges of the first three. This discussion results in a set of criteria for successful neural control mechanisms. Then, I develop my account through analyzing neuroscientific models of decision-making and control with the theoretical lenses provided by formal decision and social choice theories. I contend that neural processes can be productively modeled as a collective of agents, and neural self-organization is analogous to democratic self-governance. In particular, I show that the basal ganglia, a set of subcortical structures, contribute to the production of coherent and intelligent behaviors through implementing “democratic" procedures. Unlike the Fodorian central system—which is a micro-managing “neural commander-in-chief”—the basal ganglia are a “central election commission.” They delegate control of habitual behaviors to other distributed control mechanisms. Yet, when novel problems arise, they engage and determine the result on the basis of simple information (the votes) from across the system with the principles of neurodemocracy, and control with simple commands of inhibition and disinhibition. By actively managing and taking advantage of the wisdom-of-the-crowd effect, these democratic processes enhance the intelligence and coherence of the mind’s final "collective" decisions. I end by defending this account from both philosophical and empirical criticisms and showing that it meets the criteria for successful solution. (shrink)
The principle of self-organization has acquired a fundamental significance in the newly emerging field of computational philosophy. Self-organizing systems have been described in various domains in science and philosophy including physics, neuroscience, biology and medicine, ecology, and sociology. While system architecture and their general purpose may depend on domain-specific concepts and definitions, there are (at least) seven key properties of self-organization clearly identified in brain systems: 1) modular connectivity, 2) unsupervised learning, 3) adaptive ability, 4) (...) functional resiliency, 5) functional plasticity, 6) from-local-to-global functional organization, and 7) dynamic system growth. These are defined here in the light of insight from neurobiology, cognitive neuroscience and Adaptive Resonance Theory (ART), and physics to show that self-organization achieves stability and functional plasticity while minimizing structural system complexity. A specific example informed by empirical research is discussed to illustrate how modularity, adaptive learning, and dynamic network growth enable stable yet plastic somatosensory representation for human grip force control. Implications for the design of “strong” artificial intelligence in robotics are brought forward. (shrink)
The intuitive difference between a system that choreographs the motion of its parts in the service of goals of its own formulation and a system composed of a collection of parts doing their own thing without coordination has been shaken by now familiar examples of self-organization. There is a broad and growing presumption in parts of philosophy and across the sciences that the appearance of centralized information-processing and control in the service of system-wide goals is mere appearance, i.e., (...) an explanatory heuristic we have evolved to predict behavior, but one that will eventually get swept away in the advancing tide of self-organization. I argue that there is a distinction of central importance here, and that no adequate science of complex systems can dispense with it. (shrink)
Four articles in this issue of topiCS (volume 4, issue 1) argue against a computational approach in cognitive science in favor of a dynamical approach. I concur that the computational approach faces some considerable explanatory challenges. Yet the dynamicists’ proposal that cognition is self-organized seems to only go so far in addressing these challenges. Take, for instance, the hypothesis that cognitive behavior emerges when brain and body (re-)configure to satisfy task and environmental constraints. It is known that for certain (...) systems of constraints, no procedure can exist (whether modular, local, centralized, or self-organized) that reliably finds the right configuration in a realistic amount of time. Hence, the dynamical approach still faces the challenge of explaining how self-organized constraint satisfaction can be achieved by human brains and bodies in real time. In this commentary, I propose a methodology that dynamicists can use to try to address this challenge. (shrink)
Division of labor and its associated phenomena have been viewed as prime examples of group-level adaptations. However, the adaptations are the result of the process of evolution by natural selection and thus require that groups of insects once existed and competed for reproduction, some of which had a heritable division of labor while others did not. We present models, based on those of Kauffman (1984) that demonstrate how division of labor may occur spontaneously among groups of mutually tolerant individuals. We (...) propose that division of labor itself is not a product of natural selection but instead is a "typical" outcome of selforganization. (shrink)
This paper approaches dreaming consciousness through an examination of the self-organizing properties of the sleeping brain. This view offers a step toward reconciliation between brain-based and content-based attempts to understand the nature of dreaming. Here it is argued that the brain can be understood as a complex self-organizing system that in dreaming responds to subtle influences such as residual feelings and memories. The hyper-responsiveness of the brain during dreaming is viewed in terms of the tendency of complex chaotic-like (...) systems to respond to small variations in initial conditions and to the amplification of subtle emotional and cognitive signals through the mechanism of stochastic resonance, all in combination with psychophysiological changes in the brain during both slow wave sleep and REM sleep dreaming. Such changes include the active inhibition of extroceptive stimulation and, especially in REM sleep, alterations in the brain's dominant neuromodulatory systems, bombardment of the visual cortex with bursts of PGO activity, increases in limbic system activity, and a reduction of activity in the prefrontal regions. (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)
Contemporary complexity theory has been instrumental in providing novel rigorous definitions for some classic philosophical concepts, including emergence. In an attempt to provide an account of emergence that is consistent with complexity and dynamical systems theory, several authors have turned to the notion of constraints on state transitions. Drawing on complexity theory directly, this paper builds on those accounts, further developing the constraint-based interpretation of emergence and arguing that such accounts recover many of the features of more traditional accounts. We (...) show that the constraint-based account of emergence also leads naturally into a meaningful definition of self-organization, another concept that has received increasing attention recently. Along the way, we distinguish between order and organization, two concepts which are frequently conflated. Finally, we consider possibilities for future research in the philosophy of complex systems, as well as applications of the distinctions made in this paper. (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 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)
Historical aspects of the issue are also broached. Intuitions relative to self-organization can be found in the works of such key Western philosophical figures as Aristotle, Leibniz and Kant. Interacting with more recent authors and cybernetics, self-organization represents a notion in keeping with the modern world’s discovery of radical complexity. The themes of teleology and emergence are analyzed by philosophers of sciences with regards to the issues of modelization and scientific explanation. (publisher, edited).
The understanding of emergent, self-organizing phenomena has been immensely deepened in recent years on the basis of simulation-based theoretical research. We discuss these new ideas, and illustrate them using examples from several fields. Our discussion serves to introduce equivalent self-organized phenomena in social interaction. Interaction systems appear to be structured partly by virtue of such emergents. These appear under specific conditions: When cognitive buffering is inadequate relative to the levels of stress persons are subjected to, anxiety-spreading has the (...) potential of pushing their interaction into nonlinear conditions. Arousal in these conditions produces effects on behavior arising from biological sources-indeed, behavior can come under the control of reflex patterns. When this occurs, psychological activity no longer screens off biological controls over behavior. As the direct effects of biological activity spill into interaction, attachment behavior introduced into an interaction system can produce effects that are transmitted beyond dyads to produce global social patterns. These effects illustrate how strong interactions based in biological activity can produce an architecture for social systems. (shrink)
Following a suggestion from Warren Weaver, we extend the Shannon model of communication piecemeal into a complex systems model in which communication is differentiated both vertically and horizontally. This model enables us to bridge the divide between Niklas Luhmann’s theory of the self-organization of meaning in communications and empirical research using information theory. First, we distinguish between communication relations and correlations among patterns of relations. The correlations span a vector space in which relations are positioned and can be (...) provided with meaning. Second, positions provide reflexive perspectives. Whereas the different meanings are integrated locally, each instantiation opens global perspectives – ‘horizons of meaning’ – along eigenvectors of the communication matrix. These next-order codifications of meaning can be expected to generate redundancies when interacting in instantiations. Increases in redundancy indicate new options and can be measured as local reduction of prevailing uncertainty. The systemic generation of new options can be considered as a hallmark of the knowledge-based economy. (shrink)
Nature abounds in compound individuals. Discrete, functioning entities are made up of components which are, in some sense, also individuals. Scientists sometimes need to be concerned with whether aggregates (e.g.. species of plants) or components (e.g., quarks) exist. but such questions are not generally regarded as having great importance for science. It has often happened, however, that scientific developments have had major significance for subsequent philosophical discussion of problems of the one and the many. Recently, there has been considerable increase (...) in scientific understanding of spontaneous development of spatial and temporal organization (structure) in physical. chemical, and biological systems. In an earlier note (PS 11:35), I suggested that this progress in science raises points that may be helpful in dealing with a question of current importance for process philosophy. This paper provides support for that suggestion. The first section introduces the philosophical problem. The middle sections provide brief non-technical introduction to scientific concepts. The final section combines both topics. (shrink)
AS IS WELL KNOWN, one of Kant's major concerns was the reconciliation of Newtonian science and metaphysics, a preoccupation made particularly acute by the need to provide a satisfactory explanation of organisms. It is in light of his claim that only the mechanistic principles of Newton's physics can provide scientific knowledge that the role to be played by purposiveness becomes problematic. Purpose appears to resist mechanistic explanation and is therefore a major impediment to unifying science under one set of principles. (...) Kant concludes that although organisms cannot be explained mechanistically, the impossibility is due to a limitation of reason. By appealing to the critical turn Kant thus avoids an antinomy between mechanism and finality while allowing that it is possible for mechanism and finality to be reconciled in the supersensible. This reconciliation, unfortunately, we will never know. (shrink)
'Selforganization' is a popular theme in current studies of human social activity, enterprises, and information technology (IT). This document introduces one well developed theory of selforganization (autopoietic theory) and discusses its application to enterprises and their management.
Some biochemical systems require multiple, well-matched parts in order to function, and the removal of any of the parts eliminates the function. I have previously labeled such systems "irreducibly complex," and argued that they are stumbling blocks for Darwinian theory. Instead I proposed that they are best explained as the result of deliberate intelligent design. In a recent article Shanks and Joplin analyze and find wanting the use of irreducible complexity as a marker for intelligent design. Their primary counterexample is (...) the Belousov-Zhabotinsky reaction, a self-organizing system in which competing reaction pathways result in a chemical oscillator. In place of irreducible complexity they offer the idea of "redundant complexity," meaning that biochemical pathways overlap so that a loss of one or even several components can be accommodated without complete loss of function. Here I note that complexity is a quantitative property, so that conclusions we draw will be affected by how well-matched the components of a system are. I also show that not all biochemical systems are redundant. The origin of non-redundant systems requires a different explanation than redundant ones. (shrink)
This article reviews the seven “visions” of evolution proposed by Depew and Weber , concluding that each posited relationship between natural selection and self-organization has suited different aims and approaches. In the second section of the article, we show that these seven viewpoints may be collapsed into three fundamentally different ones: natural selection drives evolution; self-organization drives evolution; and natural selection and self-organization are complementary aspects of the evolutionary process. We then argue that these (...) three approaches are not mutually exclusive, since each may apply to different stages of development of different systems. What emerges from our discussion is a more encompassing view: that self-organization proposes what natural selection disposes. (shrink)
We can observe self-organization properties in various systems. However, modern networked dynamical sociotechnical systems have some features that allow for realizing the benefits of self-organization in a wide range of systems in economic and social areas. The review examines the general principles of self-organized systems, as well as the features of the implementation of self-organization in sociotechnical systems. We also delve into the production systems, in which the technical component is decisive, and social (...) networks, in which the social component dominates; we analyze models used for modeling self-organizing networked dynamical systems. It is shown that discrete models prevail at the micro level. Furthermore, the review deals with the features of using continuous models for modeling at the macro level. (shrink)
Complex system studies are a growing area of central importance to a wide range of disciplines, ranging from physics to politics and beyond. Adopting this interdisciplinary approach, Systems, Self-Organisation and Information presents and discusses a range of ground-breaking research in complex systems theory. Building upon foundational concepts, the volume introduces a theory of Self-Organization, providing definitions of concepts including system, structure, organization, functionality, and boundary. Biophysical and cognitive approaches to Self-Organization are also covered, discussing (...) the complex dynamics of living beings and the brain, and self-organized adaptation and learning in computational systems. The convergence of Peircean philosophy with the study of Self-Organization also provides an original pathway of research, which contributes to a dialogue between pragmatism, semeiotics, complexity theory, and self-organizing systems. As one of the few interdisciplinary works on systems theory, relating Self-Organization and Information Theory, Systems, Self-Organisation and Information is an invaluable resource for researchers and postgraduate students interested in complex systems theory from related disciplines including philosophy, physics, and engineering. (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)
The philosophical foundations of the theory of molecular self-organization (TMS) are reconstructed and compared with the explicit methodological statements made by occasions by its author(s). Special attention is paid to those philosophical fundamentals of TMS which can turn out helpful in answering the question evoking vivid discussions in the philosophy of nature of the recent decades: whether it is possible to search for a physico-chemical explanation of the genesis of life and at the same time defend its specific (...) character. In other words: do the latest findings in self-organization of prebiological molecules allow to overcome the traditional disjunction “either physics or evolution” and to replace it with the conjunction “physics and evolution”? (shrink)
There are many reasons for questioning the relevance of the concepts of self-organization (SO) and emergence. By studying three types of SO, respectively related to ontogeny, phylogeny and formalized models, we show that we always have to suppose an associated hetero-organization and preconceived immergence, unconsciously present in the authors mind. In order to understand how these unusual couples are working, they must be considered as agonistic antagonistic couples. Heteroorganization and immergence put constraints on the system so that (...) SO and emergence will produce new patterns and forms, depending on these constraints. Besides, such couples (SO and heteroorganization, emergence and immergence) seem to belong to a series of couples of the same type, allowing us to define a kind of model of life.The concept of self-organization has been presented as the main concept defining systemics, and second order cybernetics. This concept has been accepted also in general Biological Theory (BT) where authors endowed the key to many phenomena until then poorly understood. (shrink)
In this paper we aim to show that phenomenal consciousness is realized by a particular level of brain operational organization and that understanding human consciousness requires a description of the laws of the immediately underlying neural collective phenomena, the nested hierarchy of electromagnetic fields of brain activity – operational architectonics. We argue that the subjective mental reality and the objective neurobiological reality, although seemingly worlds apart, are intimately connected along a unified metastable continuum and are both guided by the (...) universal laws of the physical world such as criticality, self-organization and emergence. (shrink)
Knowing only what is empirically knowable can't by itself entail knowledge of what consciousness "is like." But if dualism is to be avoided, the question arises: how can a process be completely empirically unobservable when all of its components are completely observable? The recently emerging theory of self-organization offers resources with which to resolve this problem: Consciousness can be an empirically unobservable process because the emotions motivating attention are experienced only from the perspective of the one whose phenomenal (...) states are executed by the self-organizing processes which themselves constitute the consciousness. I argue that a self-organizing process can differ from the sum of its (empirically observable) substrata because, rather than just being realized by them, it actively rearranges the background conditions under which alternative component causal sequences can realize the self-organizing pattern into the future. (shrink)
Recent neurophysiological observations are giving rise to the expectation that in the near future genuine biological experiments may contribute more than will premature speculations to the understanding of global and cognitive functions. The classical reflex principle — as the basis of neural functions — has to yield to new ideas, like autopoiesis and/or self-organization, as the basic paradigm in the framework of which the essence of the neural can be better understood. Neural activity starts in the very earliest (...) stages of development well before receptors and afferent input become functional. Under suitable conditions, both in nervous tissue cultures and in embryonic tissue recombination experiments, the conditions of such initial autopoietic activity can be studied. This paper tries to generalize this elementary concept for various neural centers, notably for the spinal segmental apparatus and the cerebral cortex. (shrink)
Explores the acquisition and use of knowledge for human purposes and the extent of our ability to shape the future through the design, regulation, and restructuring of the lives of human systems at all levels.
Bering makes a good case for turning attention to an organized system that provides the self with transcendental meaning. In focusing on the evolutionary basis of this system, however, he overlooks the self-organizing properties of cognitive systems themselves. We propose that the illusory system Bering describes can be more generally and parsimoniously viewed as an emergent by-product of self-organization, with no need for specialized “illusion by design.”.
Foremost among the tasks facing a semiotically-informed modeling of natural open systems is the recognition and representation of self-organization. This forces attention on process, time, and energetics to complement the conventional semiotic bias toward structure, space, and informatics. While self -organization might be captured in numerous operational idioms, we suggest that the fundamentally distinctive formal structures of (a) development (intrinsic predictability) and (b) evolution (unexpected change through change in contextual meaning) constitute thewarp and woof of virtually (...) all observations on systems undergoing change, and that, since these represent complementary orientations toward phenomena generally, interaction of these styles of change within systems can lead to generic models of enormous utility in many fields. (shrink)
The relevance of the study is due to the need of theoretical and methodological interpretation of the relationship between freedom and responsibility, chaos and order in the frame of the synergetic philosophy of history in implementing the law of self-organization of intersubjective ideals under new social conditions.