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. (2008), 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 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)

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)

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)

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)

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)

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)

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)

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 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)

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)

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)

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)

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)

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.

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.

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)

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)

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)

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)

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)

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...

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)

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)

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)

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)

Computer simulations constitute a significant scientific tool for promoting scientific understanding of natural phenomena and dynamic processes. Substantial leaps in computational force and software engineering methodologies now allow the design and development of large-scale biological models, which – when combined with advanced graphics tools – may produce realistic biological scenarios, that reveal new scientific explanations and knowledge about real life phenomena. A state-of-the-art simulation system termed Reactive Animation (RA) will serve as a study case to examine the contemporary philosophical (...) debate on the scientific value of simulations, as we demonstrate its ability to form a scientific explanation of natural phenomena and to generate new emergent behaviors, making possible a prediction or hypothesis about the equivalent real-life phenomena. (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)

In this paper the central ideas and history of the theory of complex systems are described. It is shown how this theory lends itself to different interpretations and, correspondingly, to different political conclusions.

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)

Consciousness has been the bone of contention for philosophers throughout centuries. Indian philosophy largely adopted lived experience as the starting point for its explorations of consciousness. For this reason, from the very beginning, experience was an integral way of grasping consciousness, whose validity as a tool was considered self-evident. Thus, in Indian philosophy, the question was not to move from the brain to mind but to understand experience of an individual and how such an experience is determined through mental structures (...) (and secondarily, the preoccupation with the brain and its relation to the mind). In contrast, cognitive science (the study of mind and cognition through 1 interdisciplinary methods, with emphasis on computational methods) found its debates soaked in discussion which primarily involved the brain and mind. Experience was not considered a primary source of information and its validity had to be established to consider it a source of information of mind. With the rise of physicalism and realization that mental states are correlative to brain states, the body was virtually neglected from involvement in understanding the mind and the attempts to reduce mind to the brain were rampant. The inability to explain subjective experience of an individual through neuroscientific findings alone has urged philosophers to explore other ways of understanding the ontology of mind. Over the last few years, embodied cognition and enactive approach have brought back the body as a central participant in this debate, providing fertile grounds to explain the relation of brain, body and mind. This paper proposes that we understand the brain as a complex system from which the mind emerges. This emergence is marked by the development of novel property of self-consciousness in human beings. The mind is a process which is embedded throughout the body and thus, the body acts as an actualizing medium for the individual. Thus, the brain is a necessary condition for the mind to be while the mind is embedded throughout the body. The brain and mind are in reciprocal causal relationship with one another, as is the body and environment with one another. In this paper, embodied cognition is understood through principles of Merleau Ponty's idea of embodiment, than through Andy Clark and Francis Varela's alone. (shrink)

Contemporary biological research has suggested that some host–microbiome multispecies systems (referred to as “holobionts”) can in certain circumstances evolve as unique biological individual, thus being a unit of selection in evolution. If this is so, then it is arguably the case that some biological adaptations have evolved at the level of the multispecies system, what we call hologenomic adaptations. However, no research has yet been devoted to investigating their nature, or how these adaptations can be distinguished from adaptations at (...) the species-level (genomic adaptations). In this paper, we cover this gap by investigating the nature of hologenomic adaptations. By drawing on the case of the evolution of sanguivory diet in vampire bats, we argue that a trait constitutes a hologenomic adaptation when its evolution can only be explained if the holobiont is considered the biological individual that manifests this adaptation, while the bacterial taxa that bear the trait are only opportunistic beneficiaries of it. We then use the philosophical notions of emergence and inter-identity to explain the nature of this form of individuality and argue why it is special of holobionts. Overall, our paper illustrates how the use of philosophical concepts can illuminate scientific discussions, in the trend of what has recently been called metaphysics of biology. (shrink)

This paper discusses the epistemic status of biology from the standpoint of the systemic approach to living systems based on the notion of biological autonomy. This approach aims to provide an understanding of the distinctive character of biological systems and this paper analyses its theoretical and epistemological dimensions. The paper argues that, considered from this perspective, biological systems are examples of emergent phenomena, that the biological domain exhibits special features with respect to other domains, and that biology as a discipline (...) employs some core concepts, such as teleology, function, regulation among others, that are irreducible to those employed in physics and chemistry. It addresses the claim made by Jacques Monod that biology as a science is marginal. It argues that biology is general insofar as it constitutes a paradigmatic example of complexity science, both in terms of how it defines the theoretical object of study and of the epistemology and heuristics employed. As such, biology may provide lessons that can be applied more widely to develop an epistemology of complex systems. (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)

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)

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)

In this article, network science is discussed from a methodological perspective, and two central theses are defended. The first is that network science exploits the very properties that make a system complex. Rather than using idealization techniques to strip those properties away, as is standard practice in other areas of science, network science brings them to the fore, and uses them to furnish new forms of explanation. The second thesis is that network representations are particularly helpful in explaining (...) the properties of non-decomposable systems. Where part-whole decomposition is not possible, network science provides a much-needed alternative method of compressing information about the behavior of complex systems, and does so without succumbing to problems associated with combinatorial explosion. The article concludes with a comparison between the uses of network representation analyzed in the main discussion, and an entirely distinct use of network representation that has recently been discussed in connection with mechanistic modeling. (shrink)

The term “Complex Systems Biology” was introduced a few years ago [Kaneko, 2006] and, although not yet of widespread use, it seems particularly well suited to indicate an approach to biology which is well rooted in complex systems science. Although broad generalizations are always dangerous, it is safe to state that mainstream biology has been largely dominated by a gene-centric view in the last decades, due to the success of molecular biology. So the one gene - one trait (...) approch, which has often proved to be effective, has been extended to cover even complex traits. This simplifying view has been appropriately criticized, and the movement called systems biology has taken off. Systems biology [Noble, 2006] emphasizes the presence of several feedback loops in biological systems, which severely limit the range of validity of explanations based upon linear causal chains (e.g. gene → behaviour). Mathematical modelling is one the favourite tools of systems biologists to analyze the possible effects of competing negative and positive feedback loops which can be observed at several levels (from molecules to organelles, cells, tissues, organs, organisms, ecosystems). Systems biology is by now a well-established field, as it can be inferred by the rapid growth in number of conferences and journals devoted to it, as well as by the existence of several grants and funded projects.Systems biology is mainly focused upon the description of specific biological items, like for example specific organisms, or specific organs in a class of animals, or specific genetic-metabolic circuits. It therefore leaves open the issue of the search for general principles of biological organization, which apply to all living beings or to at least to broad classes. We know indeed that there are some principles of this kind, biological evolution being the most famous one. The theory of cellular organization also qualifies as a general principle. But the main focus of biological research has been that of studying specific cases, with some reluctance to accept (and perhaps a limited interest for) broad generalizations. This may however change, and this is indeed the challenge of complex systems biology: looking for general principles in biological systems, in the spirit of complex systems science which searches for similar features and behaviours in various kinds of systems. The hope to find such general principles appears well founded, and I will show in Section 2 that there are indeed data which provide support to this claim. Besides data, there are also general ideas and models concerning the way in which biological systems work. The strategy, in this case, is that of introducing simplified models of biological organisms or processes, and to look for their generic properties: this term, borrowed from statistical physics, is used for those properties which are shared by a wide class of systems. In order to model these properties, the most effective approach has been so far that of using ensembles of systems, where each member can be different from another one, and to look for those properties which are widespread. This approach was introduced many years ago [Kauffman, 1971] in modelling gene regulatory networks. At that time one had very few information about the way in which the expression of a given gene affects that of other genes, apart from the fact that this influence is real and can be studied in few selected cases (like e.g. the lactose metabolism in E. coli). Today, after many years of triumphs of molecular biology, much more has been discovered, however the possibility of describing a complete map of gene-gene interactions in a moderately complex organism is still out of reach. Therefore the goal of fully describing a network of interacting genes in a real organism could not be (and still cannot be) achieved. But a different approach has proven very fruitful, that of asking what are the typical properties of such a set of interacting genes. Making some plausible hypotheses and introducing some simplifying assumptions, Kauffman was able to address some important problems. In particular, he drew attention to the fact that a dynamical system of interacting genes displays selforganizing properties which explain some key aspects of life, most notably the existence of a limited number of cellular types in every multicellular organism (these numbers are of the order of a few hundreds, while the number of theoretically possible types, absent interactions, would be much much larger than the number of protons in the universe). In section 3 I will describe the ensemble based approach in the context of gene regulatory networks, and I will show that it can describe some important experimental data. Finally, in section 4 I will discuss some methodological aspects. (shrink)

This paper examines the complexity of the interconnection of varna and caste systems in Indian society. It reflects the complexities of the traditions of different caste groups and the system that regulates their relationship with each other. It will also reflect on the modes where they turn slightly flexible and become harshly rigid. The concept of community no longer exists. However, it is a stronger claim but is made while stressing the importance of the social Purushārtha Sādhana. Both terms (...) (caste and varna) are used interchangeably. However, a question regarding their meaning would need an entire book to be written. Both words are too ambiguous, especially for non-Indians or non-Hindus, though everyone, including Hindus and Indians, may find it challenging to distinguish between them. (shrink)

In the last 20 years, a stream of research emerged under the label of „complex problem solving“ (CPS). This research was intended to describe the way people deal with complex, dynamic, and intransparent situations. Complex computer-simulated scenarios were as stimulus material in psychological experiments. This line of research lead to subtle insights into the way how people deal with complexity and uncertainty. Besides these knowledge-rich, realistic, intransparent, complex, dynamic scenarios with many variables, a second line of (...) research used more simple, knowledge-lean scenarios with a low number of variables („minimal complex systems“, MCS) that have been proposed recently in problem-solving research for the purpose of educational assessment. In both cases, the idea behind the use of microworlds is to increase validity of problem solving tasks by presenting interactive environments that can be explored and controlled by participants while pursuing certain action goals. The main argument presented here is: both types of systems - CPS and MCS – can only be dealt with successfully if causal dependencies between input and output variables are identified and used for system control. System knowledge is necessary for control and intervention. But CPS and MCS differ in their way of how causal dependencies are identified and how the mental model is constructed; therefore, they cannot be compared directly to each other with respect to the cognitive processes that are necessary for solving the tasks. Knowledge-poor MCS tasks address only a small fraction of the cognitive processes and structures needed for knowledge-rich CPS situations. (shrink)

Museums lose their conceptual complexity and polysemy under conditions of war, forced confrontation, and struggles for survival, which may lead to a loss of diversity in the long run. Parametric General Systems analysis allows us to consider a museum as a system and to explore substratum, structural, and conceptual types of simplicity and complexity. Such qualitative analysis makes it possible to move the discussion from the ideological and value sphere to the field of rational and science-based justification. This justification, (...) in turn, illustrates why it is important to maintain complex interpretations in Ukrainian museums during the current war. (shrink)

The possibility of social and technological collapse has been the focus of science fiction tropes for decades, but more recent focus has been on specific sources of existential and global catastrophic risk. Because these scenarios are simple to understand and envision, they receive more attention than risks due to complex interplay of failures, or risks that cannot be clearly specified. In this paper, we discuss the possibility that complexity of a certain type leads to fragility which can function as (...) a source of catastrophic or even existential risk. The paper first reviews a hypothesis by Bostrom about inevitable technological risks, named the vulnerable world hypothesis. This paper next hypothesizes that fragility may not only be a possible risk, but could be inevitable,and would therefore be a subclass or example of Bostrom’s vulnerable worlds. After introducing the titular fragile world hypothesis, the paper details the conditions under which it would be correct, and presents arguments for why the conditions may in fact may apply. Finally, the assumptions and potential mitigations of the new hypothesis are contrasted with those Bostrom suggests. (shrink)

Comprehensive when it was published in 1990, this guide brought together information on the broad spectrum of education and research opportunities then available in the sciences of complexity. Its purpose was to make these kinds of investigations more accessible by providing information on programs, institutions, organizations, and literature where one can learn about their principles, methods, and applications. The guide was intended to help interested students and educators locate the various academic fields, departments, institutes, and programs that offer education in (...) systems thinking and complex systems research. The guide also served professionals who are already involved in the systems sciences as a directory to general activity in what are otherwise widely separate fields. By browsing the guide one can get a snapshot of where education and research in systems science was happening at the time in both North America and Europe. The landscape has since massively changed so its value is mostly historical. (shrink)

The study of complex systems, although an interdisciplinary endeavor, it is considered as an integrating part of physical sciences. Contrary to the historical fact that the eld is already mature, it still lacks a clear and unambiguous denition of its main object of study. Here, I propose a denition of complex systems based on the conceptual clarications made by Edgar Morin about the bidirectional non-separability of parts and whole produced by the nature of interactions. The concept to which (...) I arrived here is clear, not circular, neither too cryptic nor to explicit, and does not include any accompanying features of the own system dened. It allows, as shown in the paper, to derive some of the main properties that such systems must have as well as to propose its mathematical formalization. (shrink)

Crossing the road within the traffic system is an example of an action human agents perform successfully day-to-day in complex systems. How do they perform such successful actions given that the behaviour of complex systems is often difficult to predict? The contemporary literature contains two contrasting approaches to the epistemology of complex systems: an analytic and a post-modern approach. We argue that neither approach adequately accounts for how successful action is possible in complex systems. Agents (...) regularly perform successful actions without obeying (explicit or implicit) algorithmic rules (as the analytic approach suggests) and without an existential leap to action (as the post-modern approach suggests). We offer an alternative: A common-sense pragmatist epistemology, one that focuses on the kind of actions making up most agents’ successful moment-to-moment actions in complex systems. Successful actions obtain when agents apply ceteris paribus rules-of-thumb during predictive and decisional practices while achieving some desired goal. (shrink)

Emergence is much discussed by both philosophers and scientists. But, as noted by Mitchell (2012), there is a significant gulf; philosophers and scientists talk past each other. We contend that this is because philosophers and scientists typically mean different things by emergence, leading us to distinguish being emergence and pattern emergence. While related to distinctions offered by others between, for example, strong/weak emergence or epistemic/ontological emergence (Clayton, 2004, pp. 9–11), we argue that the being vs. pattern distinction better captures what (...) the two groups are addressing. In identifying pattern emergence as the central concern of scientists, however, we do not mean that pattern emergence is of no interest to philosophers. Rather, we argue that philosophers should attend to, and even contribute to, discussions of pattern emergence. But it is important that this discussion be distinguished, not conflated, with discussions of being emergence. In the following section we explicate the notion of being emergence and show how it has been the focus of many philosophical discussions, historical and contemporary. In section 3 we turn to pattern emergence, briefly presenting a few of the ways it figures in the discussions of scientists (and philosophers of science who contribute to these discussions in science). Finally, in sections 4 and 5, we consider the relevance of pattern emergence to several central topics in philosophy of biology: the emergence of complexity, of control, and of goal-directedness in biological systems. (shrink)

In this paper, a framework incorporating flexibility as a characteristic is proposed for designing complex, resilient socio-ecological systems. In an interconnected complex system, flexibility allows prompt deployment of resources where they are needed and is crucial for both innovation and robustness. A comparative analysis of flexible manufacturing systems, economics, evolutionary biology, and supply chain management is conducted to identify the most important characteristics of flexibility. Evolutionary biology emphasises overlapping functions and multi-functionality, which allow a system with (...) structurally different elements to perform the same function, enhancing resilience. In economics, marginal cost and marginal expected profit are factors that are considered to be important in incorporating flexibility while making changes to the system. In flexible manufacturing systems, the size of choice sets is important in creating flexibility, as initial actions preserve more options for future actions that will enhance resilience. Given the dynamic nature of flexibility, identifying the characteristics that can lead to flexibility will introduce a crucial dimension to designing resilient and sustainable socio-ecological systems with a long-term perspective in mind. (shrink)