Nonlinear synthesis and co‐evolution of complex systems

Today a change is imperative in approaching global problems: what is needed is not arm‐twisting and power politics, but searching for ways of co‐evolution in the complex social and geopolitical systems of the world. The modern theory of self‐organization of complex systems provides us with an understanding of the possible forms of coexistence of heterogeneous social and geopolitical structures at different stages of development regarding the different paths of their sustainable co‐evolutionary development. The theory argues that the evolutionary channel to the observed increasing complexity is extremely narrow and only certain discrete spectra of relatively stable self‐maintained structures are feasible in complex systems. There exists a restricted set of ways of assembling a complex evolutionary whole from diverse parts. The law of nonlinear synthesis of complex structures reads: the integration of structures in more complex ones occurs due to the establishment of a common tempo of their evolution. On the basis of the theory, we can see not only desirable but also attainable futures.     

THE COMPLEX NONLINEAR THINKING: EDGAR MORIN'S DEMAND OF A REFORM OF THINKING AND THE CONTRIBUTION OF SYNERGETICS

Main principles of the complex nonlinear thinking which are based on the notions of the modern theory of evolution and self-organization of complex systems called also synergetics are under discussion in this article. The principles are transdisciplinary, holistic, and oriented to a human being. The notions of system complexity, nonlinearity of evolution, creative chaos, space-time definiteness of structure-attractors of evolution, resonant influences, nonlinear and soft management are here of great importance. In this connection, a prominent contribution made to system analysis and to a necessary reform of education and thinking by Edgar Morin is considered.     

Evolutionary Psychology, Cognitive Science, and Dynamical Systems: Building an Integrative Paradigm

Cognitive science, evolutionary psychology, and dynamical systems theory have all been proposed as frameworks for linking the diverse subdisciplines of psychology with one another, and with other scientific disciplines. Traditional cognitive science focused on content-free general processing and deemphasized motivation. An evolutionary perspective emphasizes the centrality of motivational systems and the specificity of mechanisms designed to solve particular recurrent problems. The evolutionary perspective provides a set of broad general principles linking diverse behaviors in humans as well as other species. The dynamic approach seeks even broader principles, searching for emergent patterns in all complex systems, whether animate or inanimate. Natural selection is itself one such broad principle, as is the broader principle of self-organization, which helps explain dynamic equilibria found in groups of humans and in diverse species linked together within ecosystems. Proponents of the major contending interdisciplines will need to build more bridges if the dream of a unifying paradigm is to be realized. This review samples some of the reasons why evolutionary psychologists, dynamical systems theorists, and traditional cognitive scientists need one another.     

Evolutionary psychology from a developmental systems perspective: comment on Lickliter and Honeycutt (2003)

Although agreeing with R. Lickliter and H. Honeycutt (2003) that evolutionary psychology lacks and should adopt a coherent developmental model to explain how evolved mechanisms become expressed in phenotypes, it is argued that adhering to the principles of developmental systems theory, despite enhancing evolutionary psychology, would not change appreciably its basic focus. The concepts of innateness and modularity, what is inherited and what evolves, as well as the possible role of developmental plasticity in the evolution of human cognition are discussed. It is proposed that evolutionary psychology can incorporate the developmental systems perspective into its theorizing, with the end result being a science that more closely reflects human nature.     

Characterizing the evolutionary dynamics of language

In a recent article Mitchener and Nowak present a model of the evolutionary dynamics of language. The model exhibits regular and chaotic oscillations in changes to the proportions of grammars spoken in a population over the course of evolution. These oscillations are within the purview of evolutionary game theory, but they suggest the lack of an evolutionarily stable strategy. Implications for self-organization across scales of adaptation are discussed.     

Intentionality in non-equilibrium systems? The functional aspects of self-organized pattern formation

Psychology is frequently confronted with mind-body issues—is there a way by which mentalist and physical approaches to cognition can be integrated? Can the intentional attributes of mind be understood in scientific terms? The authors propose that synergetics, the theory of non-linear complex systems, offers steps towards a possible solution to this conundrum. In particular, we maintain that an essential property of self-organized pattern formation lies within its functionality, this being the ability to optimize, respond and adapt ‘meaningfully’ to environmental constraints. Patterns become functional because they consume in a most efficient manner the gradients which cause their evolution, thereby making synergetic pattern formation appear ‘intentional’. We therefore posit that self-organization phenomena may afford basic explanations for the adaptive, intentional and purposive behavior of many complex systems, in particular of cognitive systems. This present approach elaborates on the second law of thermodynamics.     

The puzzle of language evolution

Linguistics must again concentrate on the evolutionary nature of language, so that language models are more realistic with respect to human natural languages and have a greater explanatory force. Multi-agent systems are proposed as a possible route to develop such evolutionary models and an example is given of a concrete experiment in the origins and evolution of word-meaning based on a multi-agent approach.     

The synergetic principles of nonlinear thinking

In order to develop further the methods of scenario building and to facilitate the paths towards a desirable and sustainable future, we cannot do without a nonlinear evolutionary thinking. The theory of self‐organization of complex systems, called also synergetics, is a scientific basis for such a thinking, the main principles of which are under consideration in the paper. Synergetics provides us with the knowledge of constructive principles of coevolution of complex social systems, coevolution of countries and geopolitical regions being at different stages of development, integration of the East and the West, the North and the South.     

Figures of Time in Evolution of Complex Systems

Owing to intensive development of the theory of self-organization of complex systems called also synergetics, profound changes in our notions of time occur. Whereas at the beginning of the 20th century, natural sciences, by picking up the general spirit of Einstein's theory of relativity, consider a geometrization as an ideal, i.e. try to represent time and force interactions through space and the changes of its properties, nowadays, at the beginning of the 21st century, time turns to be in the focus of attention. It turns to be possible to represent space through time, because synergetics shows that historical and evolutionary stages of development of a complex structure can be found now, in its present spatial configuration. A whole series of paradoxical notions, such as “the influence of the future upon the present”, a “possibility of touching of a rather remote future today”, “availability of the past and the future now, in praesenti”, “irreversibility and elements of reversibility in the course of evolutionary processes in time”, “discrete unites, quanta of time”, appear in synergetics.     

Quantum dynamics of human decision-making

A quantum dynamic model of decision-making is presented, and it is compared with a previously established Markov model. Both the quantum and the Markov models are formulated as random walk decision processes, but the probabilistic principles differ between the two approaches. Quantum dynamics describe the evolution of complex valued probability amplitudes over time, whereas Markov models describe the evolution of real valued probabilities over time. Quantum dynamics generate interference effects, which are not possible with Markov models. An interference effect occurs when the probability of the union of two possible paths is smaller than each individual path alone. The choice probabilities and distribution of choice response time for the quantum model are derived, and the predictions are contrasted with the Markov model.     

Education for Civil Society: Evolutionary Guidance and the Democratic Ideal

This article honors Bela H. Banathy's work in social systems design and acknowledges his intellectual, professional, and humanitarian gifts to the system sciences community. The author examines Banathy's epistemology of conscious self-guided evolution and how it has influenced the author's thinking and research in design of educational systems, and in particular the study of education's role as an evolutionary guidance system for civil society. Specifically, the author examines Banathy's notions of evolutionary guidance systems (EGSs) and the design inquiry process. Design conversation is elaborated as a communication method for systems design and as a medium for communicative democracy. The concepts of civil society and democracy are examined in depth, providing an etymological analysis of each as a foundation for civil society as an ideal image. Consideration is given to Banathy's ideas of democracy and the New Agoras as ethical systems for the pursuit of conscious evolution. The author presents his considerations for education as an EGS for conscious evolution of civil society.     

Rhapsodic Evolution: Essay on Exaptation and Evolutionary Pluralism

Since formulating the theory of punctuated equilibria in 1972, a group of prominent evolutionary biologists, geneticists, and paleontologists have contributed towards a significant reinterpretation of the neo-Darwinian image of evolution that had consolidated during the second half of the twentieth century. We believe a research program, which we might define as "evolutionary pluralism" or "post-Darwinism," has been outlined, one that is centered on the discovery of the complexity and multiplicity of elements that work together to produce changes in our evolutionary systems. We are talking about a three-dimensional multiplicity: a multiplicity of rhythms in evolution (i.e., the theory of punctuated equilibria); a multiplicity of evolutionary units and levels (i.e., the hierarchical theory of evolution); and a multiplicity of factors and causes in evolution (i.e., the concept of exaptation). Although the reductionistic and deterministic view of natural history interprets the intelligence of evolution as a panoptic and executory rationality, evolutionary pluralism, going back to the original flexibility of the Darwinian opus, sees in the intelligence of evolution an ingenious m tis, an imperfect but very creative, craftsmanlike cleverness. The new metaphors of change introduced by evolutionary pluralism and the consequent criticism of the adaptational paradigm offer some very interesting spin-offs for the study of evolutionary systems in widely differing fields, from theoretical economics to the cognitive sciences. I propose a particular hypothesis concerning the possibility and usefulness of expanding the concept of exaptation into a general theory of developmental processes, both in biology as well as in the cognitive sciences.     

Chaos theory and the evolution of consciousness and mind: A thermodynamic-holographic resolution to the mind-body problem

This address describes Neurological Positivism's (NP) energetic evolution of consciousness, mind, and the brain-mind relationship within a model that integrates ideas and research from chaos theory, Pribram's holonomic brain theory, evolutionary theory, and the laws of thermodynamics (the energy laws The energetic evolution and encapsulation of space-time consciousness from chaotic-holographic environments is described. Consciousness is described as a natural evolutionary space-time template of continuously generated self-referential energy patterns (algorithms). The energetic evolution of mind is described as a natural self-referential exteriorization of the algorithmic organization of consciousness in the form of culturally shared mental models. It is proposed that the brain-mind energy relationship has historically undergone and continues to undergo change, and that this change is a natural thermodynamic arrow that constitutes the evolution of culture. That is, the evolution of culture proceeds in the direction of progressively more complete and efficient exteriorizations of the algorithmic organization of the brain-thus, for example, the recent evolution of brain-like computing systems and virtual reality systems. Accordingly, an uneven, but closing, central-energy-state identity (self-similarity) between brain and mind is described. It is concluded that NP's conception of mind helps us understand the evolutionary unfoldment of culture, and provides a sense of direction as to its future.     

Universal Plotkinism: A Review Of Henry Plotkin’s Darwin Machines And The Nature of Knowledge

Plotkin's Darwin Machines and the Nature of Knowledge (1993) is a major contribution to the field of evolutionary epistemology and universal Darwinism. Evolutionary epistemology is the idea that evolution is a knowledge‐gaining process. Universal Darwinism holds that processes of variation and selection can be observed at different levels from the primary level of biological evolution (where genes code for phenotypes) through to individual learning and culture (where the units of variation and selection are not so clear cut). Although antithetical to behaviorism, large parts of Plotkin's thesis can be recast in nonmentalistic terms and exploited by behavior analysts. In particular, Plotkin's arguments for a strong commonality of process between biological evolution and individual learning offer directions for progress on questions that have long interested behavior analysts, such as: Why do some organisms learn? How did learning evolve? What is the relation between behavior and evolution? Although the paths of connection between evolution and individual behavior that Plotkin sketches are not yet fully clear of confusion, his is undoubtedly a very stimulating direction to explore.     

Design and Sociocultural Evolution: Theoretical and Practical Considerations

The two approaches described here may clarify the role of design in sociocultural evolution by making best use of information already available. The first, holistic in nature, explores possible advantages of a convergence between the design, systems, and social evolution communities which, to date, have worked largely in isolation of one another. The benefits of juxtaposing the three disciplines are examined by reviewing three works on social evolution for their insights into design practice. The second approach is reductionist in nature, and proposes working across the evolutionary literatures of disciplines contiguous with design, again in order to quickly inform design practice. The two approaches are considered complementary rather than exclusionary.     

Emergent complexity: What uphill analysis or downhill invention cannot do

In these notes we review emergent phenomena in complex systems, emphasizing ways to identify potential underlying universal mechanisms that generate complexity. The discussion focuses on the emergence of collective behavior in dynamical systems when they are poised near a critical point of a phase transition, either by tuning or by self-organization. We then present the rationale for our proposal that the brain is naturally poised near criticality and review recent results as well as the implications of this view of the functioning brain.     

The Dynamics of General Developmental Mechanisms: From Piaget and Vygotsky to Dynamic Systems Models

Dynamic systems theory conceives of development as a self-organizational process. Both complexity and order emerge as a product of elementary principles of interaction between components involved in the developmental process. This article presents a dynamic systems model based on a general dual developmental mechanism, adapted from Piaget and Vygotsky. The mechanism consists of a conservative force, further strengthening the already-consolidated level, and a progressive force, consolidating internal contents and procedures at more advanced levels. It is argued that this dual mechanism constitutes one of the few basic laws of learning and change, and is comparable to the laws of effect and of contiguity. Simulation studies suggest that this dual mechanism explains self-organization in developmental paths, including the emergence of discrete jumps from one equilibrium level to another, S-shaped growth, and the occurrence of co-existing levels.     

Inquiry into intentional systems I: Issues in ecological physics

Summary The role of intention in guiding the behavior of goal-directed systems is a problem that continues to challenge behavioral science. While it is generally agreed that intentional systems must be consistent with the laws of physics, there are many obvious differences between inanimate, physical systems and sentient, intentional systems. This suggests that there must be constraints over and above those of physics that govern goal-directed behavior. In this paper it is suggested that generic properties of self-organizing mechanisms may play a central role in the origin and evolution of intentional constraints. The properties of self-organizing systems are first introduced in the context of simple physical systems and then extended to a complex (biological) system. Whereas behavior of an inanimate physical system is lawfully determined by force fields, behavior of an animate biological system is lawfully specified by information fields. Biological systems are distinguished from simple physical systems in terms of their ubiquitous use of information fields as special (biological and psychological, social, etc.) boundary conditions on classical laws. Unlike classical constraints (boundary conditions), informational constraints can vary with time and state of the system. Because of the nonstationarity of the boundary conditions, the dynamic of the system can follow a complex trajectory that is organized by a set of spatially and temporally distributed equilibrium points or regions. It is suggested that this equilibrium set and the laws that govern its transformation define a minimal requirement for an intentional system. One of the benefits of such an approach is that it suggests a realist account for the origin of semantic predicates, thereby providing a basis for the development of a theory of symbolic dynamics. Therefore, the principles of self-organization provide a comprehensive basis for investigating intentional systems by suggesting how it is that intentions arise, and by providing a lawful basis for intentional behavior that reveals how organisms become and remain lawfully informed in the pursuit of their goals.