This article attempts to show why an experimental hypothesis is plausible and merits testing; in brief, the hypothesis is that autism begins with a failure in early learning and that changing the environment of early learning would dramatically change its incidence. Strong statistical evidence supporting this hypothesis has been published by Waldman et al., but to date this evidence has largely been ignored, perhaps because it challenges prevalent beliefs about autism. This article also suggests that the current epidemic of autism (...) is serious enough, and intellectually mysterious enough, to merit attention from a wider community of brain scientists: New ideas are needed. A confirmation of this article’s hypothesis would have interesting implications for brain science. (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)

This article explores the relationship between deliberative democracy, the Internet, and systems theory’s thoughts on diversity. After introducing Habermas’s theory of deliberative democracy and how diversity fits into it, the article discusses various ideas about whether and how it could work on the Internet. Next, the article looks at research into diversity done in the field of complex adaptive systems, showing that diversity has both good and bad effects, but is clearly preferred for the purpose of survival. The (...) article concludes with an analysis of how the results of systems theory’s study of diversity can assist society in bringing democracy to the Web. (shrink)

In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an (...) intelligent manner according to the behavior of the student. An evaluation of the intelligent tutoring system has revealed reasonably acceptable results in terms of its usability and learning abilities are concerned. (shrink)

Historical processes exert an influence on the current state and evolution of situations of language contact, brought to bear from different domains, the economic and the political, the ideological and group identities, geo-demographics, and the habits of inter-group use. Clearly, this kind of phenomenon requires study from a complexical and holistic perspective in order to accommodate the variety of factors that belong to different levels and that interrelate with one another in the evolving dynamic of human languaging. Therefore, there is (...) a need for the restricted and general complexity approaches to come to a meeting of the minds, and take steps toward a mutual integration based on the acceptance of the shortcomings of each approach, achieving progress through a non-contradictory complementarity of perspectives. It must be conceded that the practical and methodological applications of basic complexical ideas need to be developed much farther in order to apply them to specific research. At the same time, the limits of complex adaptive systems as computational strategies must be accepted in the pursuit of a better understanding of the dynamic and evolutionary processes typical of human beings. New tools for the conception, apprehension and treatment of the data will need to be devised to complement existing ones and to enable us to make headway toward practices that better fit complexical perspectives. It seems obvious that human complexics must be seen as multi-methodological, insofar as necessary combining quantitative-computation methodologies and more qualitative methodologies aimed at understanding the historical mental and emotional world of people. (shrink)

This paper explores some of the factors that make complex systems complex. We first examine the history of complex systems. It was Aristotle’s insight that how elements are joined together helps determine the properties of the resulting whole. We find (a) that scientific reductionism does not provide a sufficient explanation; (b) that to understand complex systems, one must identify and trace energy flows; and (c) that disproportionate causality, including global tipping points, are all around us. Disproportionate (...) causality results from the wide availability of energy stores. We discuss three categories of emergent phenomena—static, dynamic, and adaptive—and recommend retiring the term emergent, except perhaps as a synonym for creative. Finally, we find that virtually all communication is stigmergic. (shrink)

In this article I present an alternative philosophy of science based on ideas drawn from the study of complex adaptive systems. As a result of the spectacular expansion in scientific disciplines, the number of scientists and scientific institutions in the twentieth century, I believe science can be characterised as a complex system. I want to interpret the processes of science through which scientists themselves determine what counts as good science. This characterisation of science as a (...) class='Hi'>complex system can give an answer to the question why the sciences are so successful in solving growing numbers of problems and correcting their own mistakes. I utilise components of complexity theory to explain and interpret science as a complex system. I first explain the concept of complexity in ordinary language. The explanation of science as a complex system starts with a definition of the basic rules that guide the behaviour of science as a complex system. Next, I show how various sciences result through the implementation of these rules in the study of a specific aspect of reality. The explanation of the growth of science through evolutionary adaptation and learning forms the core of the article. (shrink)

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)

This study considers the problem of using approximate way for realizing the neural supervisor for nonlinear multivariable systems. The Nonlinear Autoregressive-Moving Average (NARMA) model is an exact transformation of the input-output behavior of finite-dimensional nonlinear discrete time dynamical organization in a hoodlum of the equilibrium state. However, it is not convenient for intention of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate technique are used for realizing the neural supervisor (...) to overcome computational complexity. In this study, we introduce two classes of ideal which are approximations to the NARMA model and which are linear in the control input, namely NARMA-L1 and NARMA-L2. The latter fact substantially simplifies both the theoretical breakdown as well as the practical request of the controller. Extensive imitation studies have shown that the neural controller designed using the proposed approximate models perform very well and in dozens situation even better than an approximate controller designed using the exact NARMA Model. In view of their mathematical tractability as well as their fate in simulation studies, a matter is made in this study that such approximate input-output paragon warrants a detailed study in their own right. (shrink)

In this article, we propose some fundamental requirements for the appearance of adaptivity. We argue that a basic metabolic organization, taken in its minimal sense, may provide the conceptual framework for naturalizing the origin of teleology and normative functionality as it appears in living systems. However, adaptivity also requires the emergence of a regulatory subsystem, which implies a certain form of dynamic decoupling within a globally integrated, autonomous system. Thus, we analyze several forms of minimal adaptivity, including the special (...) case of motility. We go on to explain how an open-ended complexity growth of motility-based adaptive agency, namely, behavior, requires the appearance of the nervous system. Finally, we discuss some implications of these ideas for embodied robotics. (shrink)

The Complex Emergent Model of Language Acquisition (CEMLA) offers a new perspective on how humans acquire language, drawing on principles from complexity theory to explain this dynamic, adaptive process. Moving beyond linear and reductionist models, CEMLA views language acquisition as a system of interconnected nodes, feedback loops, and emergent patterns, operating at the edge of chaos. This framework captures the fluidity and adaptivity of language learning, highlighting how understanding and fluency arise through self-organisation, phase transitions, and interaction (...) with diverse linguistic input. By embracing the complexity of language acquisition, CEMLA provides a comprehensive model that reflects the true nature of human communication. (shrink)

Objectives: Machine learning (ML) has the potential to facilitate “continual learning” in medicine, in which an ML system continues to evolve in response to exposure to new data over time, even after being deployed in a clinical setting. In this article, we provide a tutorial on the range of ethical issues raised by the use of such “adaptive” ML systems in medicine that have, thus far, been neglected in the literature. -/- Target audience: The target audiences for this (...) tutorial are the developers of ML AI systems, healthcare regulators, the broader medical informatics community, and practicing clinicians. -/- Scope: Discussions of adaptive ML systems to date have overlooked the distinction between 2 sorts of variance that such systems may exhibit—diachronic evolution (change over time) and synchronic variation (difference between cotemporaneous instantiations of the algorithm at different sites)—and underestimated the significance of the latter. We highlight the challenges that diachronic evolution and synchronic variation present for the quality of patient care, informed consent, and equity, and discuss the complex ethical trade-offs involved in the design of such systems. (shrink)

This Thesis presents a model of cognitive development inspired by Piaget's "Genetic Epistemology". It is observed that the epigenetic process described by Piaget posess mechanisms and behaviour that characterise complex adaptive systems. A model of bipedal motion based around the "Bucket Brigade" algorithm of Holland is presened to explore this relationship.

Achieving Coherence introduces a transformative framework for understanding and managing the complexities of dynamic systems. In a world where uncertainty and interconnected challenges define the landscape, the SPARC framework (Spectrum of Possibility and Recursive Choice) offers a unified model to address these issues, bridging the gap between theory and application across disciplines. This work explores the principles of coherence, constraint satisfaction, and recursive feedback, shedding light on how systems maintain stability and adapt in the face of evolving constraints and environmental (...) noise. By integrating dimensional transitions, multi-constraint optimization, and resilience to stochastic influences, SPARC provides a novel approach to modeling systems that are inherently complex and interdependent. Applications range from stabilizing critical infrastructure and managing ecosystems under stress to advancing artificial intelligence and optimizing multi-agent systems. By demonstrating how local behaviors interact with global dynamics and how systems can thrive under variability, Achieving Coherence presents a compelling vision for navigating complexity and driving innovation in an interconnected world. (shrink)

In “What Does Environmental Protection Protect?” Mark Sagoff argues that there is no ecological way to test the claim that natural ecosystems are complex adaptive systems. In this critical commentary, I recreate that argument, object to it, and attempt to clarify its normative upshot. I show that Sagoff relies on substantive assumptions about (1) the tools and methods of ecological science, (2) what can be done with those tools and methods, and (3) ecology’s being separable from other disciplines, (...) all of which are controversial and in need of defense. I also identify five different ways that one might interpret the action-guiding recommendation that Sagoff wants to make on the basis of that argument, and I explain why all five are somewhat problematic. (shrink)

A general mathematical framework, based on countable partitions of Natural Numbers [1], is presented, that allows to provide a Semantics to propositional languages. It has the particularity of allowing both the valuations and the interpretation Sets for the connectives to discriminate complexity of the formulas. This allows different adequacy criteria to be used to assess formulas associated with the same connective, but that differ in their complexity. The presented method can be adapted potentially infinite number of connectives and truth values, (...) therefore, it can be considered a general framework to provide semantics to several of the known logic systems (eg, LC, L3 LP, FDE). The presented semantics allow to converge to different standard semantics if the separation complexity procedure is annulled. Therefore, it can be understood as a framework that allows greater precision (in complexity terms) with respect to formula satisfaction. Naturally, because of how it is built, it can be incorporated into non-deterministic semantics. The presented procedure also allows generating valuations that grant a different truth value to each formula of propositional language. As a positive side effect, our method allows a constructive proof of the equipotence between N and N^n for all Natural n. (shrink)

Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us (...) better understand the nature of complex systems in general. -/- Questions surrounding climate science can be divided into three rough categories: foundational, methodological, and evaluative questions. "How do we know that we can trust science?" is a paradigmatic foundational question (and a surprisingly difficult one to answer). Because the global climate is so complex, questions like "what makes a system complex?" also fall into this category. There are a number of existing definitions of `complexity,' and while all of them capture some aspects of what makes intuitively complex systems distinctive, none is entirely satisfactory. Most existing accounts of complexity have been developed to work with information-theoretic objects (signals, for instance) rather than the physical and social systems studied by scientists. -/- Dynamical complexity, a concept articulated in detail in the first third of the dissertation, is designed to bridge the gap between the mathematics of contemporary complexity theory (in particular the formalism of "effective complexity" developed by Gell-Mann and Lloyd [2003]) and a more general account of the structure of science generally. Dynamical complexity provides a physical interpretation of the formal tools of mathematical complexity theory, and thus can be used as a framework for thinking about general problems in the philosophy of science, including theories, explanation, and lawhood. -/- Methodological questions include questions about how climate science constructs its models, on what basis we trust those models, and how we might improve those models. In order to answer questions about climate modeling, it's important to understand what climate models look like and how they are constructed. Climate model families are significantly more diverse than are the model families of most other sciences (even sciences that study other complex systems). Existing climate models range from basic models that can be solved on paper to staggeringly complicated models that can only be analyzed using the most advanced supercomputers in the world. I introduce some of the central concepts in climatology by demonstrating how one of the most basic climate models might be constructed. I begin with the assumption that the Earth is a simple featureless blackbody which receives energy from the sun and releases it into space, and show how to model that assumption formally. I then gradually add other factors (e.g. albedo and the greenhouse effect) to the model, and show how each addition brings the model's prediction closer to agreement with observation. After constructing this basic model, I describe the so-called "complexity hierarchy" of the rest of climate models, and argue that the sense of "complexity" used in the climate modeling community is related to dynamical complexity. -/- With a clear understanding of the basics of climate modeling in hand, I then argue that foundational issues discussed early in the dissertation suggest that computation plays an irrevocably central role in climate modeling. "Science by simulation" is essential given the complexity of the global climate, but features of the climate system--the presence of non-linearities, feedback loops, and chaotic dynamics--put principled limits on the effectiveness of computational models. This tension is at the root of the staggering pluralism of the climate model hierarchy, and suggests that such pluralism is here to stay, rather than an artifact of our ignorance. Rather than attempting to converge on a single "best fit" climate model, we ought to embrace the diversity of climate models, and view each as a specialized tool designed to predict and explain a rather narrow range of phenomena. Understanding the climate system as a whole requires examining a number of different models, and correlating their outputs. This is the most significant methodological challenge of climatology. -/- Climatology's role contemporary political discourse raises an unusually high number of evaluative questions for a physical science. The two leading approaches to crafting policy surrounding climate change center on mitigation (i.e. stopping the changes from occurring) and adaptation (making post hoc changes to ameliorate the harm caused by those changes). Crafting an effective socio-political response to the threat of anthropogenic climate change, however, requires us to integrate multiple perspectives and values: the proper response will be just as diverse and pluralistic as the climate models themselves, and will incorporate aspects of both approaches. I conclude by offering some concrete recommendations about how to integrate this value pluralism into our socio-political decision making framework. (shrink)

Economies are complicated systems encompassing micro behaviors, interaction patterns, and global regularities. Whether partial or general in scope, studies of economic systems must consider how to handle difficult real-world aspects such as asymmetric information, imperfect competition, strategic interaction, collective learning, and the possibility of multiple equilibria. Recent advances in analytical and computational tools are permitting new approaches to the quantitative study of these aspects. One such approach is Agent-based Computational Economics (ACE), the computational study of economic processes modeled as dynamic (...) systems of interacting agents. This chapter explores the potential advantages and disadvantages of ACE for the study of economic systems. General points are concretely illustrated using an ACE model of a two-sector decentralized market economy. Six issues are highlighted: Constructive understanding of production, pricing, and trade processes; the essential primacy of survival; strategic rivalry and market power; behavioral uncertainty and learning; the role of conventions and organizations; and the complex interactions among structural attributes, institutional arrangements, and behavioral dispositions. (shrink)

The author interprets three stories from recently Neolithic cultures (Melanesian, African Bushman, and Inuit) and a fourth story from an oral tradition of Haitian women. All four are about women and perhaps, judging by their content, composed by women. The author trained with Edward Whitmont and developed his interpretation technique in decades of practice with dreams as a Jungian analyst. He adds a new tool, the use of repetition, in which the same point is made by a series of different (...) details. Repetition provides an internal test for the accuracy of an interpretation. The author updates Jung’s concept of archetypes to incorporate an understanding of Darwinian evolution (which Jung lacked), new knowledge of the function of genes, and new knowledge of the emergence of complexity in dynamic and adaptive systems. He compares his interpretations of the four stories with other scholars’ interpretations, in particular the extraordinary work of Michael Wessels on African Bushman legends. Though Wessels criticized Jung for imposing his ‘colonial’ theory of universal archetypes, both Jung and Wessels insisted that interpretation requires a dialogue between two agents in which both are subjects, neither being dominated or objectified. In the four stories, the author shows, symbolic consciousness began with women. The anthropologist Chris Knight proposed something similar in 1991 in his controversial book Blood Relations: Menstruation and the Origins of Culture. (shrink)

The challenges of the Anthropocene are growing ever more complex and uncertain, underpinned by the emergence of systemic risks. At the same time, the landscape of risk governance has become compartmentalised and siloed, characterized by non-overlapping activities, competing scientific discourses, and distinct responsibilities distributed across diverse public and private bodies. Operating across scales and disciplines, actors tend to work in silos which constitute critical gaps within the interface of science, policy, and practice. Yet, increasingly complex and ‘wicked’ problems (...) require holistic solutions, multi-scalar communication, coordination, collaboration, data interoperability, funding, and stakeholder engagement. To address these problems in a real-world context, we present the Risk-Tandem framework for bridging theory and practice; to guide and structure the integration of disaster risk management (DRM), climate change adaptation (CCA) and systemic risk management through a process of transdisciplinary knowledge co-production. Advancing the frontiers of knowledge in this regard, The Risk-Tandem framework combines risk management approaches and tools with iterative co-production processes as a cornerstone of its implementation, in efforts to promote the co-design of fit-for-purpose solutions, methods and approaches contributing toward strengthened risk governance alongside stakeholders. The paper outlines how the framework is developed, applied, and further refined within selected case study regions, including Denmark, Germany, Italy and the Danube Region. (shrink)

In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an (...) intelligent manner according to the behavior of the student. An evaluation of the intelligent tutoring system has revealed reasonably acceptable results in terms of its usability and learning abilities are concerned. (shrink)

Understanding everyday behavior relies heavily upon understanding our ability to improvise, how we are able to continuously anticipate and adapt in order to coordinate with our environment and others. Here we consider the ability of musicians to improvise, where they must spontaneously coordinate their actions with co-performers in order to produce novel musical expressions. Investigations of this behavior have traditionally focused on describing the organization of cognitive structures. The focus, here, however, is on the ability of the time-evolving patterns of (...) inter-musician movement coordination as revealed by the mathematical tools of complex dynamical systems to provide a new understanding of what potentiates the novelty of spontaneous musical action. We demonstrate this approach through the application of cross wavelet spectral analysis, which isolates the strength and patterning of the behavioral coordination that occurs between improvising musicians across a range of nested time-scales. Revealing the sophistication of the previously unexplored dynamics of movement coordination between improvising musicians is an important step towards understanding how creative musical expressions emerge from the spontaneous coordination of multiple musical bodies. (shrink)

This paper aims to provide a theoretical framework for explaining the subjective character of pain experience in terms of what we will call ‘embodied predictive processing’. The predictive processing (PP) theory is a family of views that take perception, action, emotion and cognition to all work together in the service of prediction error minimisation. In this paper we propose an embodied perspective on the PP theory we call the ‘embodied predictive processing (EPP) theory. The EPP theory proposes to explain pain (...) in terms of processes distributed across the whole body. The prediction error minimising system that generates pain experience comprises the immune system, the endocrine system, and the autonomic system in continuous causal interaction with pathways spread across the whole neural axis. We will argue that these systems function in a coordinated and coherent manner as a single complex adaptive system to maintain homeostasis. This system, which we refer to as the neural-endocrine-immune (NEI) system, maintains homeostasis through the process of prediction error minimisation. We go on to propose a view of the NEI ensemble as a multiscale nesting of Markov blankets that integrates the smallest scale of the cell to the largest scale of the embodied person in pain. We set out to show how the EPP theory can make sense of how pain experience could be neurobiologically constituted. We take it to be a constraint on the adequacy of a scientific explanation of subjectivity of pain experience that it makes it intelligible how pain can simultaneously be a local sensing of the body, and, at the same time, a more global, all-encompassing attitude towards the environment. Our aim in what follows is to show how the EPP theory can meet this constraint. (shrink)

Ontologies are being used by information scientists in order to facilitate the sharing of meaningful information. However, computational ontologies are problematic in that they often decontextualize information. The semantic content of information is dependent upon the context in which it exists and the experience through which it emerges. For true semantic interoperability to occur among diverse information systems, within or across domains, information must remain contextualized. In order to bring more context to computational ontologies, we introduce culture as an essential (...) concept for information science. Culture helps to focus our attention on and make meaning of relevant extrapersonal structures and their qualities and dimensions that comprise the context and background of the world. In our approach, culture is integral to the study of semantics and, consequently, the study of ontologies and information technologies. The meaning we make of entities and phenomena in the world is always shaped by our cultural experience. If we understand culture as the emergent interplay of intrapersonal cognitive structures and extrapersonal structures of the world, then the notion of cognitive and cultural schemas becomes essential to understanding ontology and the ways in which we might achieve authentic semantic interoperability among diverse information systems. We explore the nature of ontologies and reconceptualize them as cultural schemas. Our proposal is an alternative to the historical path from philosophical ontology to computational ontologies as one that adheres primarily to the notion of ontology as a categorization and classification system. The obvious implication for ontology as categorization is that there is a single objective world that exists and that it can be described as entirely separate from the person observing it. We draw upon Heidegger’s examination of ontology to ground ontology in a phenomenological perspective, enabling it to remain flexible and adaptable and to accommodate context. (shrink)

In this paper we suggest a clarification in relation to the notions of computational and intrinsic emergence, by showing how the latter is deeply connected to the new Logical Openness Theory, an original extension of Gödel theorems to the model theory. The epistemological scenario we are going to make use of is that of the theory of vision, a particularly instructive one. In order to reach our goal we introduce a dynamic theory of relationship between the observer and the observed (...) which takes into account the co-adaptive processes as well as the ecological nature of the mind/world relations. In order to fulfill the requirements of complexity sciences, this theory assumes that the scientific activity has to be able to comprehend the adaptive dynamics between system and environment as well as the model and the context where it is applied. This leads to an adaptive epistemology based on logical openness which overcomes the thigh corners of both naïve objectivist conception and radical relativism temptations by stressing that the knowledge building is a process of continuous shifting from the “frozen” syntactical dimensions to the plurality choices which make possible for mind and world to meet each other. (shrink)

After two centuries, the Diltheyan idea of the incommensurability of the natural and social sciences remains hegemonic. Alternative visions have since been overlooked; in this regard, the Baden neo-Kantian school showed that any divergence concerns implied method and not the phenomenal object of studies. W. Windelband coined the terms “nomological” and “idiographic” to underline how each discipline can be explained as a science of both law and events. To begin, I will show how complex thinking can expand and institute (...) a general integrative frame that overcomes the assumed incommensurability. By “complex,” I mean an anti-reductionist approach to understanding and a consequent ability to reveal the phenomenal world in terms of nested self-organized systems. Social and natural systems are persistent coalescences of individual entities showing series of interduality such as unicity and multiplicity, top-down conservation and bottom-up inno- vation, constraint of law and freedom of agencies. The two instances are maintained together by the rejection of abstracted and isolated concepts and the embrace of a general principle of indeterminacy resolving the apparent contradiction within the parallelization of the extremes as two different moments of analyses rooted in the social and natural classical methods. This paper considers both a) the Positivist attempt in the XIX century to approach the study of social phenomena in terms of law and b) the emergence of a general social science embracing the principle of acasuality, adapted from the study of the subatomic phenomenal world in quantum theory. Finally, this paper sketches how complex methodology can address historical and social studies with system theory in order to overcome classical dualities such as determinism vs. freedom, social vs. individual, and top down conservation vs. bottom up innovation in the form of an integrative parallelization. (shrink)

Discursive liberal democracy might not be the best of all possible forms of government, yet in Europe it is largely accepted as such. The attractors of liberal democracy (majority rule, political equality, reasonable self-determination and an ideological framework built in a tentative manner) as well as an adequate dose of secularization (according to the doctrine of religious restraint) provide both secularist and educated religious people with the most convenient ideological framework. Unfortunately, many promoters of ideological secularization take too strong a (...) stance against the manifestation of religiosity in the public sphere. They claim that people may discuss, debate or adopt (coercive) laws and regularities only by means of secular public reasons and secular motivation. We argue that these secular restraints on the ideological framework are unfairly biased against religion, counterproductive and unreasonable. The exaggerated secular restrictions create a strict secular public sphere that appears to be a Pickwickian world suitable just for inoffensive, dull and lethargic people. Deliberately separated from the idea of truth, secular public reasons cannot sustain a complex adaptive system like discursive liberal democracy. Liberal democracy needs citizens with a strong sense of truth and with a sufficient will-power to follow both a personal ideal and a collective ideal. Religious beliefs provide people with just such a sense of truth and with the desire to have a certain kind of character. In the secularized public sphere of liberal democracy, people can manifest just educated religious beliefs that correspond to the real world and respect the principle of peaceable conduct. In the final part of the article we support the assertion that believers could and should educate their religious belief before expressing them in the public sphere. Educated religious beliefs have a wide enough propositional content, obey the moral imperative of William Clifford, are purged from all propositional components against which there is strong evidence and are consciously cultivated by the mechanism of suggestion. (shrink)

This paper integrates symbolic thought and experimental research. We hypothesized that symbolic narratives provide homeostasis for the complex adaptive system that is personality. Our interpretation of a dream was based, in part, on this hypothesis. We found that the dream retold the myth of Saturn. When, by direct experiment, we tried to falsify our interpretation, our results supported our interpretation and thereby supported our hypothesis. Previously, evidence for this hypothesis had been only anecdotal. __________________________________________ For an audio-record (...) of entire class: link is given on 1st page of the text you download from this page. (shrink)

The subject of the essay is the genesis of the evolutionary strategy of стратегииHomo sapiens(SESH)as a carrier element of the transformation of technology and ethics into the main factors of anthropogenesis and the evolution of complex, self-organizing human-dimension systems.

International regulation of autonomous weapon systems (AWS) is increasingly conceived as an exercise in risk management. This requires a shared approach for assessing the risks of AWS. This paper presents a structured approach to risk assessment and regulation for AWS, adapting a qualitative framework inspired by the Intergovernmental Panel on Climate Change (IPCC). It examines the interactions among key risk factors—determinants, drivers, and types—to evaluate the risk magnitude of AWS and establish risk tolerance thresholds through a risk matrix informed by (...) background knowledge of event likelihood and severity. Further, it proposes a methodology to assess community risk appetite, emphasizing that such assessments and resulting tolerance levels should be determined through deliberation in a multistakeholder forum. The paper highlights the complexities of applying risk-based regulations to AWS internationally, particularly the challenge of defining a global community for risk assessment and regulatory legitimization. (shrink)

We review some of the main implications of the free-energy principle (FEP) for the study of the self-organization of living systems – and how the FEP can help us to understand (and model) biotic self-organization across the many temporal and spatial scales over which life exists. In order to maintain its integrity as a bounded system, any biological system - from single cells to complex organisms and societies - has to limit the disorder or dispersion (i.e., the (...) long-run entropy) of its constituent states. We review how this can be achieved by living systems that minimize their variational free energy. Variational free energy is an information theoretic construct, originally introduced into theoretical neuroscience and biology to explain perception, action, and learning. It has since been extended to explain the evolution, development, form, and function of entire organisms, providing a principled model of biotic self-organization and autopoiesis. It has provided insights into biological systems across spatiotemporal scales, ranging from microscales (e.g., sub- and multicellular dynamics), to intermediate scales (e.g., groups of interacting animals and culture), through to macroscale phenomena (the evolution of entire species). A crucial corollary of the FEP is that an organism just is (i.e., embodies or entails) an implicit model of its environment. As such, organisms come to embody causal relationships of their ecological niche, which, in turn, is influenced by their resulting behaviors. Crucially, free-energy minimization can be shown to be equivalent to the maximization of Bayesian model evidence. This allows us to cast natural selection in terms of Bayesian model selection, providing a robust theoretical account of how organisms come to match or accommodate the spatiotemporal complexity of their surrounding niche. In line with the theme of this volume; namely, biological complexity and self-organization, this chapter will examine a variational approach to self-organization across multiple dynamical scales. (shrink)

Because of advanced automation, data exchange, and cyber-physical systems, traditional project risk management strategies are losing their effectiveness in the era of Industry 4.0. This study investigates how integrating Industry 4.0 technology into project risk management frameworks can have real-world implications. Using technologies like artificial intelligence (AI), big data analytics, and the Internet of Things (IoT), it proposes a new framework that enhances risk identification, assessment, and mitigation methods. In order to demonstrate how Industry 4.0 is transforming risk management practices, (...) this article examines real-world case studies and industry implementations. The framework addresses significant opportunities and challenges to provide practitioners with useful insights for adapting to the evolving technological context. The findings suggest that incorporating Industry 4.0 technologies can significantly improve risk management efficiency and project outcomes, offering a pathway for organizations to navigate the complexities of modern project environments. (shrink)

Human augmentation is discussed in three axes: the technological means, the ability being augmented, and the social systems that will be affected. The technological augmentations considered range from exocortical information and communication systems, to pharmaceuticals, tissue and genetic engineering, and prosthetic limbs and organs, to eventually nanomedical robotics, brain-computer interfaces and cognitive prostheses. These technologies are mapped onto the capabilities which we are in the process of enabling and augmenting, which include extending longevity and physical, sensory and cognitive abilities, and (...) enabling control over emotions, moral behavior, and spiritual experience. The impacts of augmentation on the family, education, economy, politics and religion are considered individually, but their aggregate effects will be non-linear and drive complex adaptations in the living machine that is our co-evolved techno-social civilization. (shrink)

Introduction: the neuroscientific turn in political science The observation that brains and political orders are interdependent is almost trivial. Obviously, political orders require brain processes in order to emerge and to remain in place, as these processes enable action and cognition. Conversely, every since Aristotle coined man as “by nature a political animal” (Aristotle, Pol.: 1252a 3; cf. Eth. Nic.: 1097b 11), this also suggests that the political engagements of this animal has likely consequences for its natural development, including the (...) development of its psychological functions. Given these mutual interdependencies, it is remarkable that only since the 1960s, the more general domain of ‘biopolitics’ has attracted attention though first particularly in the form of behavioral politics (Alford and Hibbing). Since then biopolitics has gained in interest, so much so that different subdomains can be identified. Indeed, a 2008 review of the field of biopolitics identified five ‘headings’ of it: “(1) the case for a ‘more biologically oriented political science’, (2) ‘biologically related’ public policy issues, (3) physiological measures of political attitudes and behaviour, (4) the influence of physiological factors on actual political behaviour, and (5) the manner in which our species’ evolutionary history has left homo sapiens genetically endowed with certain social and political behavioural tendencies” (Somit and Peterson 43). Striking is how the relation between biology and politics is taken here in a rather unidirectional way, emphasizing particularly the decisive power of biology upon politics. The reverse relation is not mentioned specifically, reflecting the field of biopolitics, perhaps until quite recently. This absence of studies of political influences on our biology may have to do with the difficulty in investigating such influences. Empirical studies in biopolitics have two foci, broadly speaking: genetics and the brain, both of which have turned out to be complex and dynamic phenomena (Alford and Hibbing). Yet the studies of genetics and brain processes have made much progress in the last few decades, thanks to the development of research instruments - like fMRI brain scanners and TMS brain stimulation instruments - and of computational tools for data analysis and the simulation of explanatory models. For the field of biopolitics it is particularly relevant that within cognitive neuroscience the study of social and political issues has witnessed an increasing interest of researchers even more recently. Indeed, aware of the enabling and mediating role of the brain regarding those issues, a truly ‘neuroscientific turn’ can be observed in the social sciences, testified for example by the emergence of the field of ‘neuropolitics’ (Connolly; Vandervalk). Developing a systematic neuropolitics or biopolitics in general is a difficult challenge because of the wealth of causal influences on and interdependencies between biological, brain, cognitive and socio-political factors. Taking a somewhat more abstract perspective, this paper focuses on the process of emerging complexity in adaptive systems, enabling those to conduct ever more complex processes. Yet, parallel to that development can be observed that such systems, or organisms, are also capable in reducing the complexity of the information they are to process. Once they’re capable of developing and adjusting such compressed and complex representations of information, those systems or organisms can handle more information faster and more efficient and adaptive, yielding important benefits to the organism in navigating its environment (Halford, Wilson and Phillips). Before focusing on the role of narrative as a cognitive strategy for such a reduction of informational complexity, I will discuss the development of stable structures and increasing complexity in dynamic systems. Such a more general perspective prepares our discussion of the structures of both narratives and politics and in doing so contributes to the explanation of their interaction. (shrink)

Highlights: -/- • -/- Proposes forward-looking approach to studying climate collapse risks. • -/- Suggests diminishing returns on climate adaptation as a collapse mechanism. • -/- Suggests strategies for sustainable adaptation pathways in face of climate change. • -/- Illustrates analysis with examples of small island states and global food security. -/- Abstract: -/- This article proposes a forward-looking approach to studying societal collapse risks related to climate change. Such an approach should indicate how to study emerging collapse risks and (...) suggest strategies for adapting to them. Our approach is based on three postulates that facilitate a forward-looking approach: (1) collapse, if it occurred, would be a lengthy process rather than an abrupt event; (2) significant collapse risks already exist in some places; and (3) diminishing returns on adaptation to intensifying climate impacts are a key driver of collapse risks. The first two postulates suggests that collapse risks can be studied in process, while the third points to strategies for adaptation pathways that avoid unsustainable diminishing returns. Applying diminishing returns to climate change adaptation, rather than sociopolitical complexity or resource extraction, is also a novel theoretical contribution to collapse literature. [Open access]. (shrink)

We present a minimum message length (MML) framework for trajectory partitioning by point selection, and use it to automatically select the tolerance parameter ε for Douglas-Peucker partitioning, adapting to local trajectory complexity. By examining a range of ε for synthetic and real trajectories, it is easy to see that the best ε does vary by trajectory, and that the MML encoding makes sensible choices and is robust against Gaussian noise. We use it to explore the identification of micro-activities within a (...) longer trajectory. This MML metric is comparable to the TRACLUS metric – and shares the constraint of abstracting only by omission of points – but is a true lossless encoding. Such encoding has several theoretical advantages – particularly with very small segments (high frame rates) – but actual performance interacts strongly with the search algorithm. Both differ from unconstrained piecewise linear approximations, including other MML formulations. (shrink)

Evolutionary theory usually neglects two variables: the changes induced in the environment by the evolving organism, and individual uniqueness in sexually reproducing species. In order to fuel its maintenance and reproduction, an organism must average a positive net energy balance vis-a-v}s its environment. It achieves this via aptations, which consist of information (i.e., the internalization of all that is predictable about the environment, including the machinery to take advantage of this information) and stored energy (to operate the machinery, including a (...) safety margin to deal with events that are unpredictable in principle). Taking advantage of a prediction, however, interferes with what has been predicted; each adaptation by the organism therefore changes its environmental target. Today's organism is adapted to yesterday's environment, and today's predator inherits yesterday's prey image. This paper attempts to show that, over evolutionary time, the persistence of this asymmetric, time-lagged relationship is owed increasingly to genetically unique individuals. Individual uniqueness as resulting from sexual reproduction is janusfaced. It endows an evolving population with both a forward-looking (promethean) and backward-looking (protean) feature. A population made up of genetically unique individuals is promethean (creative) in its ability to exploit non-homogeneous resources and respond serendipitously to environmental change via new genotypes; it is protean (elusive) in presenting a pursuer (predator or parasite) with a scattered target. Furthermore, because of the asymmetry between the winnowing of the target gene pool by the pursuer, and the genetic fixation in the pursuer of an outdated target image, the target keeps evolving away from the pursuer at a speed and in a direction that are a function of the pursuer's success. This mechanism ensures an evolutionary time lag be102 W. Sterrer tween pursuer and target, which explains escalation, the stability of asymmetric coevolutionary systems such as the life/dinner principle, and the pervasiveness of the Red Queen effect. Individuality thus both promotes and retards the speed of evolution. Having probably originated simultaneously with predation, sex-generated individuality is a self-accelerating evolutionary process that may account for much of today's organismic and environmental complexity. (shrink)

Scientists depend on complex computational systems that are often ineliminably opaque, to the detriment of our ability to give scientific explanations and detect artifacts. Some philosophers have s...

Universal Basic Income (UBI) has been proposed as a potential way in which welfare states could be made more responsive to the ever-shifting evolutionary challenges of institutional adaptation in a dynamic environment. It has been proposed as a tool of “real freedom” (Van Parijs) and as a tool of making the welfare state more efficient. (Friedman) From the point of view of complexity theory and evolutionary economics, I argue that only a welfare state model that is “polycentrically” (Polanyi, Hayek) organized (...) as an evolving network of distributed decision-making can respond to the challenges of complexity in an adaptively efficient manner. UBI has the theoretical possibility to facilitate flexible, bottom-up innovation, since a) it embodies the “rule of law” principles of generality, nondiscrimination, simplicity, and transparency, and b) it grants people widespread freedom to experiment, innovate, and deviate from established practices and norms; but whether it can be made to work as intended depends on a number of variables in its design. I situate my research in the contemporary UBI debate around automation and technological development, which I interpret creatively through the lens of contemporary evolutionary political economy. I advance a syncretic model of institutional design based upon the shared insights of the Santa Fe, Neo-Hayekian, and Neo-Schumpeterian schools of evolutionary economics that, following Adam Thierer and Michael Munger, I call the framework of Permissionless Innovation (PI). Under the PI framework, which is a development of the tradition of evolutionary liberalism (Hume, Smith, Mandeville, Mill, Hayek, Polanyi, Schumpeter, Hodgson), individuals are granted the default right to innovate without having to ask for permission, and the right to basic income, which they can use to support their right to innovate, mutate, and experiment. This framework is a liberal framework to the extent it relies on widespread human freedom as a means of fostering innovation and social learning. And it is an evolutionary framework to the extent that it seeks to facilitate evolutionary socioeconomic processes for the sake of social progress and welfare advancement. I proceed to show, through an analysis of how innovation operates in both the economy and the cultural domain, that UBI can be used as an important cornerstone of an evolutionary liberal model of “ecostructural” governance that treats the socioeconomic order as an ecological garden of spontaneous growths, adaptations, and innovations. I call this the Permissionless Innovation Universal Basic Income (PIUBI) framework. In it, the right to innovate, deviate, and mutate is upheld as the “gold standard” of institutional design whereby individuals are granted widespread freedoms combined with the provision of UBI and other innovation-fostering (carefully bound) services and regulations. In the coming decades, UBI may even enable poor people to take better advantage of Human Enhancement Technologies (HETs) and other experimental innovations. Such a framework is compatible with a fast pace of evolutionary development, but the regulatory model accompanying such a framework must be capable of responding to evolutionary lock-ins, maladaptive innovations, self-destructive behaviour on the part of UBI recipients, and the management of catastrophic and existential risks. In the end, I will have shown that the PIUBI framework can be justified as a plausible default institutional mechanism for responding to radical uncertainty, but it needs to be experimentally adapted to changing circumstances with the help of various situation-specific, polycentric, multi-level, approaches. (shrink)

Maintaining systems of military plans is critical for military effectiveness, but is also challenging. Plans will become obsolete as the world diverges from the assumptions on which they rest. If too many ad hoc changes are made to intermeshed plans, the ensemble may no longer lead to well-synchronized and coordinated operations, resulting in the system of plans becoming itself incoherent. We describe in what follows an Adaptive Planning process that we are developing on behalf of the Air Force (...) Research Laboratory (Rome) with the goal of addressing problems of these sorts through cyclical collaborative plan review and maintenance. The interactions of world state, blue force status and associated plans are too complex for manual adaptive processes, and computer-aided plan review and maintenance is thus indispensable. We argue that appropriate semantic technology can 1) provide richer representation of plan-related data and semantics, 2) allow for flexible, non-disruptive, agile, scalable, and coordinated changes in plans, and 3) support more intelligent analytical querying of plan-related data. (shrink)

Can stable regularities be explained without appealing to governing laws or any other modal notion? In this paper, I consider what I will call a ‘Humean system’—a generic dynamical system without guiding laws—and assess whether it could display stable regularities. First, I present what can be interpreted as an account of the rise of stable regularities, following from Strevens [2003], which has been applied to explain the patterns of complex systems (such as those from meteorology and statistical (...) mechanics). Second, since this account presupposes that the underlying dynamics displays deterministic chaos, I assess whether it can be adapted to cases where the underlying dynamics is not chaotic but truly random—that is, cases where there is no dynamics guiding the time evolution of the system. If this is so, the resulting stable, apparently non-accidental regularities are the fruit of what can be called statistical necessity rather than of a primitive physical necessity. (shrink)

Purpose. The creation ofan ergonomic methodical approach to the modernization of management processes of metallurgical production, which involves a human factor while developing and exploiting the difficult man-machine system and estimating the degree of implementation of ergonomic requirements at different stages of an operator’s activity planning. -/- Methodology. Ananalytical model of the organization of the research works devoted to the ergonomic modernization of man-machine systems was developed. Searching and purpose-oriented investigations at different stages of man-machine system development and (...) exploitation were modelled from the sketchy projection till the exploitation of the system. Theoretical, system analytical and experimental methods were used. -/- Findings.The results of ergonomic modernization of management processes of metallurgical production in two countries under new economic (market) conditions were discussed. The factors, which define the tension in rolling-mill operators’ activity, were exposed. Certain recommendations on modernization of the existing technology and labor organization were formulated. -/- Originality. The scientific novelty consists in the development and adaptation of the methodical approach that describes adequately the cognitive complexity and psychophysiological tension in an operator’s activity as the modernization factors of modern metallurgical production in two countries. -/- Practical value.The practical value involves the creation of an ergonomic management system of the development, exploitation and modernization of difficult men-machine systems and metallurgical production management processes. (shrink)

This selective review explores biologically inspired learning as a model for intelligent robot control and sensing technology on the basis of specific examples. Hebbian synaptic learning is discussed as a functionally relevant model for machine learning and intelligence, as explained on the basis of examples from the highly plastic biological neural networks of invertebrates and vertebrates. Its potential for adaptive learning and control without supervision, the generation of functional complexity, and control architectures based on self-organization is brought forward. Learning (...) without prior knowledge based on excitatory and inhibitory neural mechanisms accounts for the process through which survival-relevant or task-relevant representations are either reinforced or suppressed. The basic mechanisms of unsupervised biological learning drive synaptic plasticity and adaptation for behavioral success in living brains with different levels of complexity. The insights collected here point toward the Hebbian model as a choice solution for “intelligent” robotics and sensor systems. Keywords: Hebbian learning; synaptic plasticity; neural networks; self-organization; brain; reinforcement; sensory processing; robot control . (shrink)

This essay argues that scientific systems have two main functions typical to self-organising adaptive and complex systems: Exploration for and exploitation of information. The self-organising nature, or spontaneous order, of scientific systems was prominently conceived by polymath Michael Polanyi. Revisiting Polanyi’s philosophy of science reveals why scientific freedom is still today as important a value as ever, even though the notion of “freedom” itself must be revised. Namely, freedom of inquiry should serve to maintain a diverse and (...) class='Hi'>adaptive balance between exploration and exploitation. This essay argues that current trends within science policy and scientific communities, from impact assessments to targeted research funding, are often inherently biased towards advancing exploitative functions over explorative activities. Concerns are raised over whether these exploitative biases suppress the explorative nature of scientific inquiry, and thus disturb the self-organisation of scientific systems by favouring hasty and sometimes negligent exploitation. Further concerns are raised as to whether these impaired adaptive capacities of scientific systems lead to reduced resilience of broader society. Finally, Polanyi’s vision of a Society of Explorers, where free exploration is vindicated and safeguarded, is revived in a 21st century context. (shrink)

Living systems at any given moment enact a very constrained set of end‐directed and contextually appropriate actions that are self‐initiated from among innumerable possible alternatives. However, these constrained actions are not necessarily because the system has reduced its sensitivities to themselves and their surroundings. Quite the contrary, living systems are continually open to novel and unanticipated stimulations that require a physiology of coordination. To address these competing demands, this paper offers a novel heuristic model informed by neuroscience, systems theory, (...) biology and sign study to explain how organisms situated in diverse, complex and ever‐changing environments might draw upon the sparse order made available by ‘relevant noise’. This emergent order facilitates coordination, habituation and, ultimately, understanding of the world and its relevant affordances. Inspired by the burgeoning field of coordination dynamics and physiologist Denis Noble's concept of ‘biological relativity’, this model proposes a view of coordination on the neuronal level that is neither sequential nor stochastic, but instead implements a causal logic of phasic alignment, such that an organism's learned and inherited sets of diverse biological affinities and sympathies can be resolved into a continuous and complex range of patterns that will implement the kind of novel orientations and radical generativity required of such organisms to adaptively explore their environments and to learn from their experiences. (shrink)

Music and language are universal human abilities with many apparent similarities relating to their acoustics, structure, and frequent use in social situations. We might therefore expect them to be understood and processed similarly, and indeed an emerging body of research suggests that this is the case. But the focus has historically been on the individual, looking at the passive listener or the isolated speaker or performer, even though social interaction is the primary site of use for both domains. Nonetheless, an (...) important goal of emerging research is to compare music and language in terms of acoustics and structure, social interaction, and functional origins to develop parallel accounts across the two domains. Indeed, a central aim of both of evolutionary musicology and language evolution research is to understand the adaptive significance or functional origin of human music and language. An influential proposal to emerge in recent years has been referred to as the social bonding hypothesis. Here, within a comparative approach to animal communication systems, I review empirical studies in support of the social bonding hypothesis in humans, non-human primates, songbirds, and various other mammals. In support of this hypothesis, I review six research fields: (i) the functional origins of music; (ii) the functional origins of language; (iii) mechanisms of social synchrony for human social bonding; (iv) language and social bonding in humans; (v) music and social bonding in humans; and (vi) pitch, tone and emotional expression in human speech and music. I conclude that the comparative study of complex vocalizations and behaviors in various extant species can provide important insights into the adaptive function(s) of these traits in these species, as well as offer evidence-based speculations for the existence of “musilanguage” in our primate ancestors, and thus inform our understanding of the biology and evolution of human music and language. (shrink)

Functional decomposition is an important goal in the life sciences, and is central to mechanistic explanation and explanatory reduction. A growing literature in philosophy of science, however, has challenged decomposition-based notions of explanation. ‘Holists’ posit that complex systems exhibit context-sensitivity, dynamic interaction, and network dependence, and that these properties undermine decomposition. They then infer from the failure of decomposition to the failure of mechanistic explanation and reduction. I argue that complexity, so construed, is only incompatible with one notion of (...) decomposition, which I call ‘atomism’, and not with decomposition writ large. Atomism posits that function ascriptions must be made to parts with minimal reference to the surrounding system. Complexity does indeed falsify atomism, but I contend that there is a weaker, ‘contextualist’ notion of decomposition that is fully compatible with the properties that holists cite. Contextualism suggests that the function of parts can shift with external context, and that interactions with other parts might help determine their context-appropriate functions. This still admits of functional decomposition within a given context. I will give examples based on the notion of oscillatory multiplexing in systems neuroscience. If contextualism is feasible, then holist inferences are faulty—one cannot infer from the presence of complexity to the failure of decomposition, mechanism, and reductionism. (shrink)

Time and space are conflated in time-warps when asleep we dream. Our wakeful cognitive ability to keep them separate indicates different ways of envisaging self-hood. Awareness that dream-time and life-time are separate is itself a propensity of human minds that has evolved by natural selection with adaptive developments in cerebral neuronal circuitry that underpin human behavioural complexity. The contrast is highlighted between how memory of our spatio-temporal experiences appears to be treated by our brain one way when we are (...) wide-awake and thus well aware of our unfolding personal life-history, and in a different way when, fast asleep, our dreaming dissolves any such awareness and our oneiric self-hood seems different from our real-life self-hood. The difference is considered from two angles. Regarding simultaneous memory-storage for an experience recalled from alternative perspectives, a theoretical possibility is proposed of a pro-system comparable to Cantor Ternary Set topology. Regarding the brain, the difference is considered in relation to the temporo-spatial theory of consciousness and the compatible concept of active inference forestalling surprisal by minimising variational free energy according to the free energy principle. (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)

The central motivating idea behind the development of this work is the concept of prespace, a hypothetical structure that is postulated by some physicists to underlie the fabric of space or space-time. I consider how such a structure could relate to space and space-time, and the rest of reality as we know it, and the implications of the existence of this structure for quantum theory. Understanding how this structure could relate to space and to the rest of reality requires, I (...) believe, that we consider how space itself relates to reality, and how other so-called "spaces" used in physics relate to reality. In chapter 2, I compare space and space-time to other spaces used in physics, such as configuration space, phase space and Hilbert space. I support what is known as the "property view" of space, opposing both the traditional views of space and space-time, substantivalism and relationism. I argue that all these spaces are property spaces. After examining the relationships of these spaces to causality, I argue that configuration space has, due to its role in quantum mechanics, a special status in the microscopic world similar to the status of position space in the macroscopic world. In chapter 3, prespace itself is considered. One way of approaching this structure is through the comparison of the prespace structure with a computational system, in particular to a cellular automaton, in which space or space-time and all other physical quantities are broken down into discrete units. I suggest that one way open for a prespace metaphysics can be found if physics is made fully discrete in this way. I suggest as a heuristic principle that the physical laws of our world are such that the computational cost of implementing those laws on an arbitrary computational system is minimized, adapting a heuristic principle of this type proposed by Feynman. In chapter 4, some of the ideas of the previous chapters are applied in an examination of the physics and metaphysics of quantum theory. I first discuss the "measurement problem" of quantum mechanics: this problem and its proposed solution are the primary subjects of chapter 4. It turns out that considering how quantum theory could be made fully discrete leads naturally to a suggestion of how standard linear quantum mechanics could be modified to give rise to a solution to the measurement problem. The computational heuristic principle reinforces the same solution. I call the modified quantum mechanics Critical Complexity Quantum Mechanics (CCQM). I compare CCQM with some of the other proposed solutions to the measurement problem, in particular the spontaneous localization model of Ghirardi, Rimini and Weber. Finally, in chapters 5 and 6, I argue that the measure of complexity of quantum mechanical states I introduce in CCQM also provides a new definition of entropy for quantum mechanics, and suggests a solution to the problem of providing an objective foundation for statistical mechanics, thermodynamics, and the arrow of time. (shrink)