Three decades after Chalmers named it, the ‘hard problem’ remains. I suggest a parsimonious solution. Biological dynamic systems interact according to simple rules (while the environment provides simple constraints) and thus self-organize to become a new, more complex dynamic system at the next level. This spiral repeats several times generating a hierarchy of levels. A leap to the next level is frequently creative and surprising. From ants, themselves self-organized according to physical/chemical laws, may (...) emerge an ant colony self-organized according to eusocial laws. A dynamic system need not be material. A living language (immaterial) is a complex adaptive system. Body/brain are material but the next level of complexity, a psychological dynamic system, a thought, feeling, image or ideal, is less material. From several psychological dynamic systems emerges the next level, narrative (immaterial), and from multiple narratives emerges personality. Concrete evidence explains how an early narrative emerges from body-and-brain. Evidence also shows that personality emerges from narrative. Even an objective narrative captures subjectivity since the teller’s choice of content is subjective. I argue that the ‘stream-of-consciousness’ story (movie) you are currently telling yourself (watching) is your conscious experience, ‘what it is like’ for you to be conscious. Adriana Cavarero’s arguments support this. Each level of a hierarchy of dynamic systems must necessarily be homeostatic, at that level. McDowell et al. (2023: submitted, in revision) reported evidence that a dream (a narrative) supports personality homeostatically. Perhaps the evolutionary advantage of conscious experience, also a narrative, has always been that it too supports personality homeostatically. Personality and body/brain, a chimera of symbiotic life-forms, constitute interactionist duality. (shrink)

Self-organized criticality (SOC) is based upon the idea that complex behavior can develop spontaneously in certain multi-body systems whose dynamics vary abruptly. This book is a clear and concise introduction to the field of self-organized criticality, and contains an overview of the main research results. The author begins with an examination of what is meant by SOC, and the systems in which it can occur. He then presents and analyzes computer models to describe a number (...) of systems, and he explains the different mathematical formalisms developed to understand SOC. The final chapter assesses the impact of this field of study, and highlights some key areas of new research. The author assumes no previous knowledge of the field, and the book contains several exercises. It will be ideal as a textbook for graduate students taking physics, engineering, or mathematical biology courses in nonlinear science or complexity. (shrink)

In nature, gregarious animals, insects, or bacteria usually exhibit paradoxical behaviors in the form of group fission and fusion, which exerts an important influence on group’s pattern formation, information transfer, and epidemiology. However, the fission-fusion dynamics have received little attention compared to other flocking behavior. In this paper, an intermittent selective interaction based control algorithm for the self-organized fission-fusion behavior of flocking system is proposed, which bridges the gap between the two conflicting behaviors in a unified fashion. Specifically, (...) a hybrid velocity coordination strategy that includes both the egalitarian and selective interactions is proposed, where the egalitarian interaction is to maintain the flock’s order and achieve the fusion behavior while the selective interaction strategy is for the response to external stimulus information and generates the fission behavior. Numerical simulations demonstrate that the proposed control algorithm can realize the self-organized fission-fusion behavior of flocking system under a unified framework. The influences of the main control parameters on the performance of the fission-fusion behavior are also discussed. In particular, the trade-off parameterαbalances the exploration and exploitation behaviors of flocking system and significantly enhances its movement flexibility and environmental adaptivity. (shrink)

After more than 15 years of study, the 1/f noise or complex-systems approach to cognitive science has delivered promises of progress, colorful verbiage, and statistical analyses of phenomena whose relevance for cognition remains unclear. What the complex-systems approach has arguably failed to deliver are concrete insights about how people perceive, think, decide, and act. Without formal models that implement the proposed abstract concepts, the complex-systems approach to cognitive science runs the danger of becoming a philosophical exercise in (...) futility. The complex-systems approach can be informative and innovative, but only if it is implemented as a formal model that allows concrete prediction, falsification, and comparison against more traditional approaches. (shrink)

We introduce the notion of complexity, first at an intuitive level and then in relatively more concrete terms, explaining the various characteristic features of complex systems with examples. There exists a vast literature on complexity, and our exposition is intended to be an elementary introduction, meant for a broad audience. -/- Briefly, a complex system is one whose description involves a hierarchy of levels, where each level is made of a large number of components interacting among themselves. (...) The time evolution of such a system is of a complex nature, depending on the interactions among subsystems in the next level below the one under consideration and, at the same time, conditioned by the level above, where the latter sets the context for the evolution. Generally speaking, the interactions among the constituents of the various levels lead to a dynamics characterized by numerous characteristic scales, each level having its own set of scales. What is more, a level commonly exhibits ‘emergent properties’ that cannot be derived from considerations relating to its component systems taken in isolation or to those in a different contextual setting. In the dynamic evolution of some particular level, there occurs a self-organized emergence of a higher level and the process is repeated at still higher levels. -/- The interaction and self-organization of the components of a complex system follow the principle commonly expressed by saying that the ‘whole is different from the sum of the parts’. In the case of systems whose behavior can be expressed mathematically in terms of differential equations this means that the interactions are nonlinear in nature. -/- While all of the above features are not universally exhibited by complex systems, these are nevertheless indicative of a broad commonness relative to which individual systems can be described and analyzed. There exist measures of complexity which, once again, are not of universal applicability, being more heuristic than exact. The present state of knowledge and understanding of complex systems is itself an emerging one. Still, a large number of results on various systems can be related to their complex character, making complexity an immensely fertile concept in the study of natural, biological, and social phenomena. -/- All this puts a very definite limitation on the complete description of a complex system as a whole since such a system can be precisely described only contextually, relative to some particular level, where emergent properties rule out an exact description of more than one levels within a common framework. -/- We discuss the implications of these observations in the context of our conception of the so-called noumenal reality that has a mind-independent existence and is perceived by us in the form of the phenomenal reality. The latter is derived from the former by means of our perceptions and interpretations, and our efforts at sorting out and making sense of the bewildering complexity of reality takes the form of incessant processes of inference that lead to theories. Strictly speaking, theories apply to models that are constructed as idealized versions of parts of reality, within which inferences and abstractions can be carried out meaningfully, enabling us to construct the theories. -/- There exists a correspondence between the phenomenal and the noumenal realities in terms of events and their correlations, where these are experienced as the complex behavior of systems or entities of various descriptions. The infinite diversity of behavior of systems in the phenomenal world are explained within specified contexts by theories. The latter are constructs generated in our ceaseless attempts at interpreting the world, and the question arises as to whether these are reflections of `laws of nature' residing in the noumenal world. This is a fundamental concern of scientific realism, within the fold of which there exists a trend towards the assumption that theories express truths about the noumenal reality. We examine this assumption (referred to as a ‘point of view’ in the present essay) closely and indicate that an alternative point of view is also consistent within the broad framework of scientific realism. This is the view that theories are domain-specific and contextual, and that these are arrived at by independent processes of inference and abstractions in the various domains of experience. Theories in contiguous domains of experience dovetail and interpenetrate with one another, and bear the responsibility of correctly explaining our observations within these domains. -/- With accumulating experience, theories get revised and the network of our theories of the world acquires a complex structure, exhibiting a complex evolution. There exists a tendency within the fold of scientific realism of interpreting this complex evolution in rather simple terms, where one assumes (this, again, is a point of view) that theories tend more and more closely to truths about Nature and, what is more, progress towards an all-embracing ‘ultimate theory’ -- a foundational one in respect of all our inquiries into nature. We examine this point of view closely and outline the alternative view -- one broadly consistent with scientific realism -- that there is no ‘ultimate’ law of nature, that theories do not correspond to truths inherent in reality, and that successive revisions in theory do not lead monotonically to some ultimate truth. Instead, the theories generated in succession are incommensurate with each other, testifying to the fact that a theory gives us a perspective view of some part of reality, arrived at contextually. Instead of resembling a monotonically converging series successive theories are analogous to asymptotic series. -/- Before we summarize all the above considerations, we briefly address the issue of the complexity of the {\it human mind} -- one as pervasive as the complexity of Nature at large. The complexity of the mind is related to the complexity of the underlying neuronal organization in the brain, which operates within a larger biological context, its activities being modulated by other physiological systems, notably the one involving a host of chemical messengers. The mind, with no materiality of its own, is nevertheless emergent from the activity of interacting neuronal assemblies in the brain. As in the case of reality at large, there can be no ultimate theory of the mind, from which one can explain and predict the entire spectrum of human behavior, which is an infinitely rich and diverse one. (shrink)

A generalization of a Burridge-Knopoff spring-block model is investigated to illustrate the dynamics of transform faults. The model can undergo Hopf bifurcation and fold bifurcation of limit cycles. Considering the cyclical nature of the spring stiffness, the model with periodic perturbation is further explored via a continuation technique and numerical bifurcation analysis. It is shown that the periodic perturbation induces abundant dynamics, the existence, the switch, and the coexistence of multiple attractors including periodic solutions with various periods, quasiperiodic solutions, chaotic (...) solutions through torus destruction, or cascade of period doublings. Throughout the results obtained, one can see that the system manifests complex dynamical behaviors such as chaos, self-organized criticality, and the transition of dynamical behaviors when it comes to periodic perturbations. Even very small variation of a parameter can result in radical changes of the dynamics, which provides a new insight into the fault dynamics. (shrink)

A notion of delegated causality is introduced here. This subtle kind of causality is dual to interventional causality. Delegated causality elucidates the causal role of dynamical systems at the “edge of chaos”, explicates evident cases of downward causation, and relates emergent phenomena to Gödel’s incompleteness theorem. Apparently rich implications are noticed in biology and Chinese philosophy. The perspective of delegated causality supports cognitive interpretations of self-organization and evolution.

Lately there has been a growing interest in evolutionary studies concerning how the regularities and patterns found in the living cell could have emerged spontaneously by way of self-assembly and self-organization. It is reasonable to postulate that the chemical compounds found in the primitive Earth would have mostly been very simple in nature, and would have been immersed in the natural dynamics of the physical world, some of which would have involved self-organization. It seems likely that some (...) molecular processes self-organized spontaneously into a hierarchy of complex behaviours. Our conceptual search herein reaches back to the time when prebiotic phenomena began to take shape. This was before the origin of life, so in this paper we hope to shed new light on some of the theoretical issues that surround the ways in which cellular organization might have evolved without the aid of replicated information. (shrink)

This paper proposes a Cournot game organized by three competing firms adopting bounded rationality. According to the marginal profit in the past time step, each firm tries to update its production using local knowledge. In this game, a firm’s preference is represented by a utility function that is derived from a constant elasticity of substitution production function. The game is modeled by a 3-dimensional discrete dynamical system. The equilibria of the system are numerically studied to detect their complex (...) characteristics due to difficulty to get an explicit form for those equilibria. For the proposed utility function, some cases with different value parameters are considered. Numerical simulations are used to provide an experimental evidence for the complex behavior of the evolution of the system. The obtained results show that the system loses its stability due to different types of bifurcations. (shrink)

This chapter describes the application of reduction concepts in emergence and self organization of complex dynamical system. Condition-dependent laws compress and dynamical equation sets provide implicit compressed representations even when most of that information is not explicitly available without decompression. And, paradoxically, there is still the determined march of fundamental analytical dynamics expanding its compression reach toward a Theory of Everything—even while the more rapidly expanding domain of complex systems dynamics confronts its assumptions and its monolithicity. Nor (...) does science fall apart into a disunified aggregate of particular cases since, with fundamental dynamics as a backbone, complex matching up of models across theoretical and empirical domains then articulates its model-structured skeleton. Discussion provides the delicately entwined dance of emergence and reduction providing constraints on compression that also permit its expansion. However, while the vision is not dead, it is currently substantially more complexly structured through model similarities and differences than that initially envisaged and individuals are left with deep questions about compression unresolved. (shrink)

The Western metaphor of self-as-identity?as a static, inherently exclusive entity?has been instrumental, historically, to our radical separation from nature, and still hampers a reviving of genuine participation with nature. Suggesting an alternative to this metaphor (informed by literacy as technology), I explore the more nature-informed metaphor of dynamic, complex self-systems, involving both natural and human subsystems. Through this latter metaphor, I re-vision radical participation with nature: in the process of perception, in epistemology/ontology, and in the ways (...) of indigenous, oral cultures. This systems metaphor also sheds contrasting light on literacy-informed, Western ways. (shrink)

(This version was submitted to Behavioral and Brain Science. A revised version was published by Biological Theory) Estimates of autism’s incidence increased 5-10 fold in ten years, an increase which cannot be genetic. Though many mutations are associated with autism, no mutation seems directly to cause autism. We need to find the direct cause. Complexity science provides a new paradigm - confirmed in biology by extensive hard data. Both the body and the personality are complex dynamic systems which (...) spontaneously self-organize from simple dynamic systems. Autism may therefore be caused by the failure of a simple dynamic system. We know that infants who cannot track their mother’s face often become autistic, that eye-contact initiates intersubjectivity which is blocked in autism, and that the infant-mother pair seems designed to promote eye-contact, as does the eye’s appearance. This author earlier proposed that failure of eye-contact might directly cause autism and that early non-maternal childcare, including television/video, would therefore be statistically linked to autism. Waldman et al. (2008; 2006) recently proved that autism is strongly linked to precipitation (indoor activity) and to the introduction of cable. The most plausible explanation? Early exposure to television/video is linked to autism. Furthermore a normal developmental cascade (blocked in autism) has been deciphered: (a) Infant-mother eye-contact triggers increased maternal attention. (b) Early maternal attention permanently increases not only baseline vasopressin but also that oxytocin release which is triggered by subsequent maternal attention. (c) Vasopressin and oxytocin promote face recognition, gazing-at-the-eyes, emotion recognition, and social bonding. The eye-contact hypothesis suggests a clinical study addressing prevention: recruit prospective parents who agree to curtail television/video/computer/wi-fi in their families; measure autism’s incidence in their children. (shrink)

The Autism Spectrum Disorder (ASD) represents a set of life-long disorders. In particular, subjects with ASD can display momentary behaviors of acute agitation and aggressiveness called crisis behaviors. These events are problematic for the subject and care providers but little is known about their occurrence, namely, possible relations among intensity, frequency, and duration. A group of ASD subjects (n=33) has been observed for 12 months reporting data on each crisis ( n = 1137 crises). Statistical analysis did not find significant (...) results, while the relation between crisis duration and frequency showed a good fit to a “power law” curve, suggesting the application of Self-Organized Criticality (SOC) model. The SOC is used to describe natural phenomena as earthquakes, bank failures of rivers, mass extinctions, and other systems where a type of “catastrophic events” is necessary to maintain a critical equilibrium. In a sense, subjects at risk of crisis behavior seem to fit the same model as seismic zones at risk of earthquakes. The employment of the same strategies, as those successfully developed for known SOC systems, could lead to important insights for ASD management. Moreover, the SOC model offers possible interpretations of crisis behavior dynamics suggesting that they are unpredictable and, in a sense, necessary. (shrink)

Self-organized complexity in the physical, biological, and social sciences Donald L Turcotte*f and John B. Rundle* *Department of Earth and Atmospheric ...

Dynamics of complex systems is often hierarchically organized on different time scales. To understand the physics of such hierarchy, here Brownian motion of a particle moving through a fluctuating medium with slowly varying temperature is studied as an analytically tractable example, and a kinetic theory is formulated for describing the states of the particle. What is peculiar here is that the (inverse) temperature is treated as a dynamical variable. Dynamical hierarchy is introduced in conformity with the (...) adiabatic scheme. Then, a new analytical method is developed to show how the Fokker–Planck equation admits as a stationary solution the Maxwellian distribution modulated by the temperature fluctuations, the distribution of which turns out to be determined by the drift term. A careful comment is also made on so-called superstatistics. (shrink)

The emphasis placed by H. Atlan, like G. Bateson, on the reception of messages during communication between subsystems leads to a conception of learning, and more generally of human memory, surprisingly close to that proposed by I. Rosenfield on the basis of the work of G. M. Edelman. The authors stressed the close and reciprocal link between the theory of functional localization and the conception of memory, which they have just seen, radically refuted by Rosenfield. The theory of functional localization (...) therefore considers as established the existence of a whole series of rigid relationships between specific locations in the brain and certain major functions performed by the body. Thus briefly summarized, the theory of neural Darwinism provides positive evidence in favor of the Rosenfield's theory of human memory. All these characteristics make the functioning of human memory an outstanding example of the natural complexity of a self‐organized system in the sense of Atlan. (shrink)

The sense of self has always been a topic of high interest in both psychoanalysis and most recently in neuroscience. Nowadays, there is an agreement in psychoanalysis that the self emerges from the relationship with the other (e.g., the caregiver) in terms of his/her capacity to attune, regulate, and synchronize with the emergent self of the infant. The outcome of this relational/intersubjective synchronization is the development of the sense of self and its regulatory processes both in (...) dynamic psychology and neuroscience. In this work, we propose that synchrony is a fundamental biobehavioral factor in these dialectical processes between self and others which shapes the brain–body–mind system of the individuals, including their sense of self. Recently in neuroscience, it has been proposed by the research group around Northoff that the self is constituted by a brain-based nested hierarchical three-layer structure, including interoceptive, proprio-exteroceptive, and mental layers of self. This may be disrupted, though, when traumatic experiences occur. Following the three levels of trauma theorized by Mucci, we here suggest how different levels of traumatic experiences might have an enduring effect in yielding a trauma-based topographic and dynamic re-organization of the nested model of self featured by dissociation. In conclusion, we propose that different levels and degrees of traumatic experience are related to corresponding disruptions in the topography and dynamic of the brain-based three-layer hierarchical structure of the self. (shrink)

Let us start by some general definitions of the concept of complexity. We take a complex system to be one composed by a large number of parts, and whose properties are not fully explained by an understanding of its components parts. Studies of complex systems recognized the importance of “wholeness”, defined as problems of organization (and of regulation), phenomena non resolvable into local events, dynamics interactions in the difference of behaviour of parts when isolated or in higher configuration, (...) etc., in short, systems of various orders (or levels) not understandable by investigation of their respective parts in isolation. In a complex system it is essential to distinguish between ‘global’ and ‘local’ properties. Theoretical physicists in the last two decades have discovered that the collective behaviour of a macro-system, i.e. a system composed of many objects, does not change qualitatively when the behaviour of single components are modified slightly. Conversely, it has been also found that the behaviour of single components does change when the overall behaviour of the system is modified. There are many universal classes which describe the collective behaviour of the system, and each class has its own characteristics; the universal classes do not change when we perturb the system. The most interesting and rewarding work consists in finding these universal classes and in spelling out their properties. This conception has been followed in studies done in the last twenty years on second order phase transitions. The objective, which has been mostly achieved, was to classify all possible types of phase transitions in different universality classes and to compute the parameters that control the behaviour of the system near the transition (or critical or bifurcation) point as a function of the universality class. This point of view is not very different from the one expressed by Thom in the introduction of Structural Stability and Morphogenesis (1975). It differs from Thom’s program because there is no a priori idea of the mathematical framework which should be used. Indeed Thom considers only a restricted class of models (ordinary differential equations in low dimensional spaces) while we do not have any prejudice regarding which models should be accepted. One of the most interesting and surprising results obtained by studying complex systems is the possibility of classifying the configurations of the system taxonomically. It is well-known that a well founded taxonomy is possible only if the objects we want to classify have some unique properties, i.e. species may be introduced in an objective way only if it is impossible to go continuously from one specie to another; in a more mathematical language, we say that objects must have the property of ultrametricity. More precisely, it was discovered that there are conditions under which a class of complex systems may only exist in configurations that have the ultrametricity property and consequently they can be classified in a hierarchical way. Indeed, it has been found that only this ultrametricity property is shared by the near-optimal solutions of many optimization problems of complex functions, i.e. corrugated landscapes in Kauffman’s language. These results are derived from the study of spin glass model, but they have wider implications. It is possible that the kind of structures that arise in these cases is present in many other apparently unrelated problems. Before to go on with our considerations, we have to pick in mind two main complementary ideas about complexity. (i) According to the prevalent and usual point of view, the essence of complex systems lies in the emergence of complex structures from the non-linear interaction of many simple elements that obey simple rules. Typically, these rules consist of 0–1 alternatives selected in response to the input received, as in many prototypes like cellular automata, Boolean networks, spin systems, etc. Quite intricate patterns and structures can occur in such systems. However, what can be also said is that these are toy systems, and the systems occurring in reality rather consist of elements that individually are quite complex themselves. (ii) So, this bring a new aspect that seems essential and indispensable to the emergence and functioning of complex systems, namely the coordination of individual agents or elements that themselves are complex at their own scale of operation. This coordination dramatically reduces the degree of freedom of those participating agents. Even the constituents of molecules, i.e. the atoms, are rather complicated conglomerations of subatomic particles, perhaps ultimately excitations of patterns of superstrings. Genes, the elementary biochemical coding units, are very complex macromolecular strings, as are the metabolic units, the proteins. Neurons, the basic elements of cognitive networks, themselves are cells. In those mentioned and in other complex systems, it is an important feature that the potential complexity of the behaviour of the individual agents gets dramatically simplified through the global interactions within the system. The individual degrees of freedom are drastically reduced, or, in a more formal terminology, the factual space of the system is much smaller than the product of the state space of the individual elements. That is one key aspect. The other one is that on this basis, that is utilizing the coordination between the activities of its members, the system then becomes able to develop and express a coherent structure at a higher level, that is, an emergent behaviour (and emergent properties) that transcends what each element is individually capable of. (shrink)

To understand how complex dynamic systems, living or non-living, linguistic or non-linguistic, come to be organized as systems, to understand how their inherent dynamic nature gives rise to organisations and forms that have found a balance between potentiality for change and evolution on the one hand, and requisite stability in a given environment on the other, is the main ambition of the study of evolutionary systems. The aim of the present volume is to elucidate the scientific (...) and philosophical backgrounds that play a role in one of the major debates taking place in that field, namely that on the relation between selection and self-organization. The book represents a genuine interdisciplinary forum in which the major representatives of evolutionary systems take part. Audience: This volume will be interest to biologists, philosophers of science, systems scientists, mathematicians, physicists, sociologists of science. It is highly recommended to those interested in an interdisciplinary and complex approach to evolution, as well as to those interested in developing a genuinely historical viewpoint in the sciences. (shrink)

The unreduced solution to the arbitrary interaction problem, absent in the standard theory framework, reveals many equally real and mutually incompatible system configurations, or "realizations". This is the essence of universal dynamic undecidability, or multivaluedness, and the ensuing causal randomness (unpredictability), non-computability, irreversible time flow (evolution, emergence), and dynamic complexity of every real system, object, or process. This creative undecidability of real-world dynamics provides causal explanations for "quantum mysteries", relativity postulates, cosmological problems, and the huge efficiency of high-complexity (...) phenomena, such as life, intelligence, and consciousness, giving rise to extended applications, far beyond the critical limits of usual science paradigm. (shrink)

We consider four mechanisms by which apparent discontinuities in the distribution of antisociality could arise: (1) executive genes or hormonal systems, (2) multiplicative interactions of predisposing factors, (3) environmental tracking into a limited number of social roles, and (4) cross-generational gene—environment interactions. A more explicit consideration of complex self-organizing dynamic systems may help us understand the maintenance of antisocial subpopulations.

Living systems employ several mechanisms and behaviors to achieve robustness and maintain themselves under changing internal and external conditions. Regulation stands out from them as a specific form of higher-order control, exerted over the basic regime responsible for the production and maintenance of the organism, and provides the system with the capacity to act on its own constitutive dynamics. It consists in the capability to selectively shift between different available regimes of self-production and self-maintenance in response to specific (...) signals and perturbations, due to the action of a dedicated subsystem which is operationally distinct from the regulated ones. The role of regulation, however, is not exhausted by its contribution to maintain a living system’s viability. While enhancing robustness, regulatory mechanisms play a fundamental role in the realization of an autonomous biological organization. Specifically, they are at the basis of the remarkable integration of biological systems, insofar as they coordinate and modulate the activity of distinct functional subsystems. Moreover, by implementing complex and hierarchically organized control architectures, they allow for an increase in structural and organizational complexity while minimizing fragility. Finally, they endow living systems, from their most basic unicellular instances, with the capability to control their own internal dynamics to adaptively respond to specific features of their interaction with the environment, thus providing the basis for the emergence of minimal forms of cognition. (shrink)

This work presents a post-positivist research framework for explaining any surprising or anomalous fact in the evolutionary path of a complex, dynamic, and contingent social process. Firstly, it elaborates on the reconciliation betweenthe ontological and epistemological assumptions of Critical Realism with the principles of American Pragmatism. Next, the research method is presented: theoretical propositions about a social structure are translated into a set of grammar rules that acknowledge patterns of sequences of events, either involving individual action or interaction (...) between actors within a real social system. The result is a discrete mathematical model for a concrete category of social process based on these rules. Finally, data-grounded refinement of the theory is possible through comparison between cases belonging to the same category, but differing in some contingent pattern of sequences of event outcomes. Consequently, their grammars differ in some pairs of context-sensitive rules that explain this surprising fact, and the derivation of this alternative historical trajectory of event outcomes becomes an extension to the early category of social process. In this sense, the proposed framework suggests a hierarchy of classes of grammars for middle-range explanations based on the ontological assumption of the generative nature of social reality. (shrink)

There is presently considerable interest in the phenomenon of "self-organisation" in dynamical systems. The rough idea of self-organisation is that a structure appears "by itself in a dynamical system, with reasonably high probability, in a reasonably short time, with no help from a special initial state, or interaction with an external system. What is often missed, however, is that the standard evolutionary account of the origin of multi-cellular life fits this definition, so that higher living organisms are also (...) products of self-organisation. Very few kinds of object can selforganise, and the question of what such objects are like is a suitable mathematical problem. Extending the familiar notion of algorithmic complexity into the context of dynamical systems, we obtain a notion of "dynamical complexity". A simple theorem then shows that only objects of very low dynamical complexity can self organise, so that living organisms must be of low dynamical complexity. On the other hand, symmetry considerations suggest that living organisms are highly complex, relative to the dynamical laws, due to their large size and high degree of irregularity. In particular, it is shown that since dynamical laws operate locally, and do not vary across space and time, they cannot produce any specific large and irregular structure with high probability in a short time. These arguments suggest that standard evolutionary theories of the origin of higher organisms are incomplete. (shrink)

Living systems employ several mechanisms and behaviors to achieve robustness and maintain themselves under changing internal and external conditions. Regulation stands out from them as a specific form of higher-order control, exerted over the basic regime responsible for the production and maintenance of the organism, and provides the system with the capacity to act on its own constitutive dynamics. It consists in the capability to selectively shift between different available regimes of self-production and self-maintenance in response to specific (...) signals and perturbations, due to the action of a dedicated subsystem which is operationally distinct from the regulated ones. The role of regulation, however, is not exhausted by its contribution to maintain a living system’s viability. While enhancing robustness, regulatory mechanisms play a fundamental role in the realization of an autonomous biological organization. Specifically, they are at the basis of the remarkable integration of biological systems, insofar as they coordinate and modulate the activity of distinct functional subsystems. Moreover, by implementing complex and hierarchically organized control architectures, they allow for an increase in structural and organizational complexity while minimizing fragility. Finally, they endow living systems, from their most basic unicellular instances, with the capability to control their own internal dynamics to adaptively respond to specific features of their interaction with the environment, thus providing the basis for the emergence of minimal forms of cognition. (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)

The Visual World Paradigm (VWP) presents listeners with a challenging problem: They must integrate two disparate signals, the spoken language and the visual context, in support of action (e.g., complex movements of the eyes across a scene). We present Impulse Processing, a dynamical systems approach to incremental eye movements in the visual world that suggests a framework for integrating language, vision, and action generally. Our approach assumes that impulses driven by the language and the visual context impinge minutely on (...) a dynamical landscape of attractors corresponding to the potential eye-movement behaviors of the system. We test three unique predictions of our approach in an empirical study in the VWP, and describe an implementation in an artificial neural network. We discuss the Impulse Processing framework in relation to other models of the VWP. (shrink)

Economic logic impinges on contemporary political theory through both economic reductionism and economic methodology applied to political decision-making (through game theory). The authors argue that the sort of models used are based on mechanistic and linear methodologies that have now been found wanting in physics. They further argue that complexity based self-organization methods are better suited to model the complexities of economy and polity and their interactions with the overall social system.

The terms complexity, complex adaptive systems, and sciences of complexity are found often in recent scientific literature, reflecting the remarkable growth in collaborative academic research focused on complexity from the origin and dynamics of organisms to the largest social and political organizations. One of the great challenges in this field of research is to discover which features are essential and shared by all of the seemingly disparate systems that are described as complex. Is there sufficient synthesis to suggest (...) the possibility of an overarching science of complexity? This report describes current views on this subject held by various eminent scholars associated with the Santa Fe Institute.The physical sciences have traditionally been concerned with “simple” systems whose dynamics can be described in mathematical terms with precision and certainty. In contrast, the biological and social sciences are inevitably concerned with self-organized or social “complex” systems whose detailed behaviors appear to be unpredictable. The two categories differ greatly in size and diversity, prompting the late mathematician Stanislaus Ulam to remark that research on complex systems might be compared to the study of non-elephants. Nevertheless, certain integrative themes have begun to emerge.Rising activity in this field of research runs completely counter to the trend toward increasing fragmentation and specialization in the sciences. It has stimulated a resurgence of interest in a broad synthesis involving mathematics, computational science, physics, chemistry, biology, neuroscience, and the social sciences. The growth of effort in this very extended field has been greatly stimulated by the development of new computational tools that are capable of dealing with vast, interrelated databases. Many of the participants in complexity research feel that it is now time to reintegrate the fragmented interests of much of the academic community. The reader is encouraged to consider whether such views are sparking a historic renaissance of scholarship or represent a passing scientific diversion. (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)

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)

This work identifies the influence of chaos theory on fractional calculus by providing a theorem for the existence and stability of solution in fractional-order gyrostat model with the help of a fixed-point theorem. We modified an integer order gyrostat model consisting of three rotors into fractional order by attaching rotatory fuel-filled tank and provided an iterative scheme for our proposed model as a working rule of obtained analytical results. Moreover, this iterative scheme is injected into algorithms for a system of (...) integer order dynamical systems to observe Lyapunov exponents and a bifurcation diagram for our proposed fractional-order dynamical model. Furthermore, we obtained five equilibrium points, including four unstable spirals and one saddle node, using local dynamical analysis which acted as self-exciting attractors and a separatrix in a global domain. (shrink)

Magnetoencephalography (MEG) and electroencephalography (EEG) are invaluable neuroscientific tools for unveiling human neural dynamics in three dimensions (space, time, and frequency), which are associated with a wide variety of perceptions, cognition, and actions. MEG/EEG also provides different categories of neuronal indices including activity magnitude, connectivity, and network properties along the three dimensions. In the last 20 years, interest has increased in inter-regional connectivity and complex network properties assessed by various sophisticated scientific analyses. We herein review the definition, computation, short (...) history, and pros and cons of connectivity and complex network (graph-theory) analyses applied to MEG/EEG signals. We briefly describe recent developments in source reconstruction algorithms essential for source-space connectivity and network analyses. Furthermore, we discuss a relatively novel approach used in MEG/EEG studies to examine the complex dynamics represented by human brain activity. The correct and effective use of these neuronal metrics provides a new insight into the multi-dimensional dynamics of the neural representations of various functions in the complex human brain. (shrink)

This commentary proposes that “cognitive control” is neither componential nor emergent, but a fundamental feature of behavior. The term “control” requires an operational definition. This is best provided by the negative feedback loop that utilizes behavior to control perception; it does not control behavior per se. In order to model complex cognitive control, Perceptual Control Theory proposes that loops are organized into a dissociable hierarchical network (PCT; Powers, Clark, & McFarland, 1960; Powers, 1973a, 2008). In this way, behavior (...) is dynamically adaptive to environmental disturbances, rather than being formed by, or superimposed upon, learned associations between stimulus and response. (shrink)

The spread of epidemics, especially COVID-19, is having a significant impact on the world. If an epidemic is not properly controlled at the beginning, it is likely to spread rapidly and widely through the coexistence relationship between natural and social systems. A university community is a special, micro-self-organized social system that is densely populated. However, university authorities in such an environment seem to be less cautious in the defence of an epidemic. Currently, there is almost no quantitative research (...) on epidemic spreading and response strategies in universities. In this paper, a case study of a university community is considered for a simulation of an infection evolving after an epidemic outbreak based on the method of system dynamics of the three stages. The results show the following: By improving the speed of the initial emergency response, the total number of patients can be effectively controlled. A quarantine policy helps to slow down the evolution of infection. The higher the isolation ratio, the higher the cost; therefore, the isolation ratio should be optimized. It is important to make emergency plans for controlling epidemic spreading and carry out emergency drills and assessments regularly. According to the results of this study, we suggest an emergency management framework for public health events in university communities. (shrink)

This study reports on action research efforts that were aimed at developing institutional arrangements beneficial for soil fertility improvement. Three stages of action research are described and analyzed. We initially began by bringing stakeholders together in a platform to engage in a collaborative design of new arrangements. However, this effort was stymied mainly because conditions conducive for learning and negotiation were lacking. We then proceeded to support experimentation with alternative arrangements initiated by individual landowners and migrant farmers. The implementation of (...) these arrangements too ran into difficulties due to intra-family dynamics and ambiguities regarding land tenure. Further investigations to find out how ambiguities could be tackled revealed that the local actors themselves had taken initiatives towards developing institutional innovations to reduce ambiguities. However, there is still considerable scope for further development of these self-organized innovations. The article ends with a reflection on inter-disciplinary action research, where it is argued that making “mistakes” is an inherent and necessary characteristic in action research that aims to address complex social issues. (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 contribution discusses competencies needed for regulating systems with properties of multi-causality and non-linear dynamics (therapeutic, economical, organizational, socio-political, technical, ecological, etc.). Various research communities have contributed insights, but none has come forward with an inclusive framework. To advance the debate, I propose to draw from dynamic systems theory (DST) and “4E” (embodied, embedded, enactive, and extended), cognition approaches, which offer a set of perspectives to understand what expert regulators in real-life settings do. They define the regulator's agency as (...) skillfully imposing constraints on a target system and hereby creating context-sensitive openings for self-organizing dynamics, rather than “controlling” the system. Adept regulators apply multi-pronged and multi-timescale constraints to achieve nuanced effects. Among other things, their skill set includes scarcely noted enactive processual competencies for “emergence management”, which the intellectualistic and insufficiently ecologically situated accounts of the complex problem solving literature omit. To capture the nature of system regulation, I advocate treating regulation dynamics and target system dynamics “symmetrically” by grounding regulator competencies in concepts from complexity theory. (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)

Mechanistic frameworks of investigation and explanation dominate the cognitive, neural, and psychological sciences. In this dissertation, I argue that mechanistic frameworks cannot, in principle, explain some kinds of cognition. In its place, I argue that complexity science has methods and theories more appropriate for investigating and explaining some cognitive phenomena. -/- I begin with an examination of the term 'cognition.' I defend the idea that "cognition" has been a moving target of investigation in the relevant sciences. As such it is (...) not historically true that there has been a thoroughly entrenched and agreed upon conception of "cognition." Next, I take up mechanistic frameworks. Although 'mechanism' is an umbrella term for a set of loosely related characteristics, there are common features: linearity, localization, and component dominance. I then describe complexity science, with emphasis on its utilization of dynamical systems modeling. Next, I discuss two phenomena that typically fall under the purview of complexity science: nonlinearity and interaction dominance. -/- A complexity science framework guided by the theory of self-organized criticality and utilizing the methods of dynamical systems modeling can surmount a number of challenges that face mechanistic frameworks when investigating some kinds of cognition. The first challenge is epistemic and concerns the inadequacy of mechanistic frameworks to facilitate the comprehensibility of massive amounts of data across various scales and areas of inquiry. I argue that complexity science is more appropriate for making big data comprehensible when investigating cognition, particularly across disciplines. I demonstrate this via an approach called nested dynamical modeling (NDM). NDM can facilitate comprehensibility of large amounts of data obtained from various scales of investigation by eliminating irrelevant degrees of freedom of that system as relates to the target of investigation. -/- The second shortcoming concerns ontological blind spots within mechanistic frameworks. Cognitive phenomena like extended cognition often fail to meet most, if not all, of the criteria assumed by many mechanistic approaches, especially component dominance. I argue that research guided by the notion of interaction dominance allows for extended cognition to be a real, empirically supported phenomenon within complex systems frameworks. In this chapter I discuss some of my experimental work on extended cognitive systems. -/- The search for mechanisms can be a reasonable starting position when attempting to explain natural phenomena in the life sciences. However, too strict of an adherence to theoretical and methodological commitments such as linearity, localization, and component dominance can result in intractable epistemic challenges and ontological blind spots. Complexity science has theories and methods to overcome such challenges in the investigation of cognition. (shrink)

Abstract. Following the tracks of Ryle and based upon the theory of complex systems, we shall develop a characterization of action-based consciousness as an embodied, embedded, selforganized process in which action and dispositions occupy a special place. From this perspective, consciousness is not a unique prerogative of humans, but it is spread all around, throughout the evolution of life. We argue that artificial systems such as robots currently lack the genuine embodied embeddedness that allows the type of self-organization (...) that is relevant to consciousness. -/- Sommario. Seguendo la linea tracciata da Ryle e basata sulla teorie dei sistemi complessi, svilupperemo una caratterizzazione della coscienza basata sull’azione come un processo incarnato, situato e auto organizzante nel quale le azioni e le disposizioni occupano un ruolo decisivo. Da questo punto di vista, la coscienza non è una prerogativa esclusiva degli esseri umani, ma è diffusa nel mondo naturale grazie ai processi evolutivi. Noi sosteniamo che i sistemi artificiali come i robot attualmente sono carenti del tipo di relazione con la corporeità e con l’ambiente che consente quel tipo di auto-organizzazione indispensabile per l’emergenza della coscienza. (shrink)

Purpose : The purpose of this paper is to bring the concept of a 'hierarchy of action', as it is currently being used in other fields, into library and information science . Design/methodology/approach Hierarchy theory is adopted to describe three hierarchies of action, which include the human processes of semantic and social innovation, as well as a system of biological interpretence, from which human processes are thought to have evolved as a development of biosemiosis in nature. By way (...) of example, it is argued that a text is a complex achievement, and hierarchy theory shows how to account for this complexity; the everyday definition of text is augmented with accounts from different levels of observation. Findings: The concept of a hierarchy of action enables a person to account for a text as a meaning/symbolic product; include in that account the processes whereby texts are produced and used; and say why these processes are important to the health of the biosphere that is called home. Originality/value Hierarchy of action has been developed as a concept in biology and ecology; it belongs to a way of thinking whereby human reality, like nature, is construed as dynamical processes operating in symbiotic relationship with each other; it has not yet been adopted in LIS with reference to hierarchy theory and its potential is yet to be explored. Keywords Hierarchy theory, Complexity theory, Process philosophy, Natural philosophy, Hierarchies of action, Complex systems, Libraries, Information science Paper type Conceptual paper. (shrink)

A summary of topics and theoretical approaches to dynamical systems and psychology. Includes chapters on physical systems, self-organization, state space and dimensionality, networks, neurodynamics, fractals and how such concepts help to explain cognition and the mind.

The ability of an agent to overcome limitations caused by complexity can be identified with intelligence. Yet, the study of complexity is dominated by the issues not really associated with authentic intelligence. In search of the methods to overcome limitations of complexity it is necessary to find a sufficiently general conceptual framework for its study, to identify its characteristics and sources, and then to explore alternatives to the currently used methods. The present paper is using for this purpose the conceptual (...) framework of information, its integration, and dynamics developed by the author in his earlier publications. Using this framework, complexity is characterized in both quantitative and qualitative ways, and in both static and dynamic perspectives. The main objective is to propose an approach to transcending limitations of complexity through reverse engineering of the effectiveness in overcoming complexity by natural, living organisms. Since the most striking characteristic of life is its hierarchic organization, the use of multi-level hierarchic information systems in information processing is explored. Theoretical design of such multi-level systems becomes possible with the use of generalized Turing machines as components performing concurrent computation on all levels of the hierarchy. (shrink)

Since the origins of the notion of emergence in attempts to recover the content of vitalistic anti-reductionism without its questionable metaphysics, emergence has been treated in terms of logical properties. This approach was doomed to failure, because logical properties are either sui generis or they are constructions from other logical properties. If the former, they do not explain on their own and are inevitably somewhat arbitrary (the problem with the related concept of supervenience, Collier, 1988a), but if the latter, reducibility (...) is assured because logical constructs are reducible, by definition, to their logical components. A satisfactory account of emergence must recognise that it is a dynamical, not a logical property of property of natural systems, and that its basis is dynamical rather than logical composition. Collier (1988a) introduced the concept of cohesion as the closure of the causal relations among the dynamical parts of a dynamical particular that determine its resistance to external and internal fluctuations that might disrupt its integrity. Cohesion is an equivalence relation that partitions a set of dynamical particulars into unified and distinct entities, providing the identity conditions for such particulars. Cohesion blocks reduction of dynamical particulars, and is necessary for dynamical emergence. We will give reasons for thinking that cohesion might be sufficient for emergence as well. (shrink)