v. 1. Origins of order-creation science : complexity science from basic disciplines -- v. 2. Self-organization, emergence and self-organized criticality -- v. 3. Organization and management complexity dynamics -- v. 4. Agent-based socio-economic simulation -- v. 5. Power-law distributions in society and business.

This article addresses complexity by selecting some of its key aspects that share a common feature: the power to change. They seem to change not only the way the world is approached by scientists, but also the way this approach, the resulting perspectives and their multiple relationships, are interpreted. These main aspects are: (1) the challenge of measurability, with an unexpected result that escapes the gravitational field of the measurability problem; (2) the meaning of reproducibility and the redrawn boundaries (...) of scientific inquiry, with implications for the social sciences; (3) the altered expectations concerning prediction, which seem to break with a glorious tradition of unquestioned technological success; and (4) the discovery of all-embracing patterns of events that unavoidably include large events, possibly perceived as ‘crises’, which one may hope to understand and confront, rather than rule out. The resulting geography, with its new landmarks, new relationships among its elements and new means of orientation, is expected to reach the public sooner or later, even if the effect – according to complexity theory itself – cannot be foreseen in detail. All these fibres of change are considered in the context of a fresh meaning of time and of a topology dominated by network concepts. (shrink)

We use a method suggested by Kolmogorov complexity to examine some relations between Kolmogorov complexity and noncomputability. In particular we show that the method consistently gives us more information than conventional ways of demonstrating noncomputability . Also, many sets which are awkward to embed into the halting problem are easily shown noncomputable. We also prove a gap-theorem for outputting consecutive integers and find, for a given length n, a statement of length n with maximal proof length.

The need to establish a research field within psychology didactics at secondary level has recently been voiced by several researchers internationally. An analysis of a Swedish case coming out of secondary level education in psychology presented here provides an illustration that complexity thinking – derived from complexity theory – is uniquely placed to consider and indicate possible solutions to challenges, described by researchers as central to the foundation of a new field. Subject-matter didactics is defined for the purpose (...) of this paper as a combination of general didactics and subject- matter content, and considering the international nature of research traditions coming out of psychology, the implications of the results presented here cannot be regarded as limited solely to national concerns. An on-line survey was sent to secondary schools in Sweden. Discussions and lectures along with teaching to the book – alternatively used as inspiration – emerged as central from the thematic analysis of the results, providing the first mapping of teaching practices in secondary level psychology in Sweden. An analysis, founded on complexity thinking – combined with a model enabling a delimitation of the scope of study – focused on time use and the importance placed on self-knowledge, along with the transformation of theory into practice. The former pointing to a teacher centred nested subsystem (e.g. asymmetric relations between teachers and students), the latter pointing to student centred nested subsystems coming out of embodied knowledge (e.g. students as node) where psychological perspectives are learnt through self-reflexion, case studies and everyday life experiences (turning theory to practice), implying a holistic approach. The analysis applied to the Swedish case provides an illustration of how complexity theory has the potential to address challenges at micro and macro level to the establishment of a new research field in psychology didactics and to indicate possible solutions. Psychologies high relevance to everyday life, multi-causality, perspective pluralism, dynamic systems character and scientific character, makes complexity thinking a relevant approach in the consideration of challenges to the establishment of a research field in didactics of psychology. (shrink)

Wherever we look, we notice complexity. Philosophically, the concept constitutes a tangled web of problems, in theory as well as daily life. Complexity and Analysis is a meticulous rendering of these problems, tackling the seldom considered nature of complexity that confronts ontological analysts and holists alike. Stewart Umphrey expertly describes the limits of analysis as they have come to light within mathematics, the natural sciences, and analytic philosophy, explaining how Aristotle came upon, and sought to move beyond, (...) the limits of ontological analysis. In trying to understand any complex entity, Umphrey argues, one succeeds in meeting the criterion of metaphysical adequacy only if one fails to meet the crietrion of epistemological adequacy. Ranging across an array of subjects including Kantian and Hegelian idealism, this book provides a superb account of how our own complexity presents not only theoretical problems, but ethical and political dilemmas of great practical significance. (shrink)

In _Complexity and Postmodernism_, Paul Cilliers explores the idea of complexity in the light of contemporary perspectives from philosophy and science. Cilliers offers us a unique approach to understanding complexity and computational theory by integrating postmodern theory into his discussion. _Complexity and Postmodernism_ is an exciting and an original book that should be read by anyone interested in gaining a fresh understanding of complexity, postmodernism and connectionism.

In a world of ever-growing specialization, the issue of complexity attracts a good amount of attention from cross-disciplinary points of view. Charles S. Peirce’s thought may help not only to shoulder once again philosophical responsibility which has been largely abdicated by much of 20th century philosophy, but also to tackle some of the most stubborn contemporary problems. The founder of pragmatism identified one century ago most of these problems, and he also mapped out some paths that may be followed (...) to overcome the poverty of contemporary scientistic reductionism. One of these paths is related with the issue of complexity that lies at the heart of all his conception. Along this line, the aim of this article is to describe what Peirce can teach about complexity to contemporary researchers from different scientific backgrounds. The article is divided in three sections: 1) a brief presentation of Peirce, stressing his personal authority as a scientist philosopher; 2) the theory of categories as the heart of complexity according to Peirce and, finally, 3) some consequences of Peirce’s notion of complexity in relation with abduction and creativity, semiosis, cross-disciplinarity and communication. (shrink)

An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in (...) divergent explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

In our article, “Syntactic complexity effects in sentence production”, we reported two elicited production experiments and argued that there is a cost associated with planning and uttering syntactically complex, object-extracted structures that contain a non-local syntactic dependency. MacDonald et al. () have argued that the results of our investigation provide little new information on the topic. We disagree. Examining the production of subject versus object extractions in two constructions across two experimental paradigms—relative clauses in Experiment 1 and wh-questions in (...) Experiment 2—we found a strikingly similar pattern: reliable differences in latency and word durations, as well as in rates of disfluencies, signaling a greater cost associated with planning and uttering the syntactically more complex object extractions. MacDonald et al. reject that interpretation, namely that the differences we observed in the production of subject versus object extractions demonstrate asymmetric production difficulties. Here we address the concerns they raise by clarifying confusion and presenting novel experimental evidence in support of our original claims. (shrink)

Designing effective computational systems is often a matter of finding ways in which simple logical operations can be combined to perform more complex tasks. Computer scientists therefore gauge the complexity of tasks by asking how many such operations would be needed to perform them. They are especially concerned with cases in which the number of these operations is so large that the task cannot feasibly be performed by computational means. This happens whenever a task that takes n bits of (...) information to specify requires X^n operations to perform. Unless n is very small, the magnitude of the computational resources that would be needed to perform such tasks exceeds anything that could plausibly be available within a brain, or that could have been available over the course of intelligence’s evolution. When intelligent creatures succeed in dealing with tasks of this sort, their success therefore cannot be explained simply by the postulation of a computation. We must instead adopt an explanatory strategy that takes into account not only the things that are intelligently done but also the bounds within which this intelligence is accomplished. The question of which tasks exhibit such complexity is among the most fundamental open questions in theoretical computer science. (shrink)

This book explains the relationship between intelligence and environmental complexity, and in so doing links philosophy of mind to more general issues about the relations between organisms and environments, and to the general pattern of 'externalist' explanations. The author provides a biological approach to the investigation of mind and cognition in nature. In particular he explores the idea that the function of cognition is to enable agents to deal with environmental complexity. The history of the idea in the (...) work of Dewey and Spencer is considered, as is the impact of recent evolutionary theory on our understanding of the place of mind in nature. (shrink)

What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of individual neurons produce something as extraordinarily complex as consciousness? What is it that guides self-organizing structures like the immune system, the World Wide Web, the global economy, and the human genome? These are just a few of the fascinating and elusive questions that the science of complexity seeks to answer. In this remarkably accessible and companionable book, leading complex (...) systems scientist Melanie Mitchell provides an intimate, detailed tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. Comprehending such systems requires a wholly new approach, one that goes beyond traditional scientific reductionism and that re-maps long-standing disciplinary boundaries. Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. She explores as well the relationship between complexity and evolution, artificial intelligence, computation, genetics, information processing, and many other fields. Richly illustrated and vividly written, Complexity : A Guided Tour offers a comprehensive and eminently comprehensible overview of the ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for the field's contribution to solving some of the most important scientific questions of our time. (shrink)

The complexity of human societies of the past few thousand years rivals that of social insect societies. We hypothesize that two sets of social “instincts” underpin and constrain the evolution of complex societies. One set is ancient and shared with other social primate species, and one is derived and unique to our lineage. The latter evolved by the late Pleistocene, and led to the evolution of institutions of intermediate complexity in acephalous societies. The institutions of complex societies often (...) conflict with our social instincts. The complex societies of the last few thousand years can function only because cultural evolution has created effective “work-arounds” to manage such instincts. We describe a series of work-arounds and use the data on the relative effectiveness of WWII armies to test the work-around hypothesis. (shrink)

The complex systems approach to cognitive science invites a new understanding of extended cognitive systems. According to this understanding, extended cognitive systems are heterogenous, composed of brain, body, and niche, non-linearly coupled to one another. This view of cognitive systems, as non-linearly coupled brain–body–niche systems, promises conceptual and methodological advances. In this article we focus on two of these. First, the fundamental interdependence among brain, body, and niche makes it possible to explain extended cognition without invoking representations or computation. Second, (...) cognition and conscious experience can be understood as a single phenomenon, eliminating fruitless philosophical discussion of qualia and the so-called hard problem of consciousness. What we call “extended phenomenological-cognitive systems” are relational and dynamical entities, with interactions among heterogeneous parts at multiple spatial and temporal scales. (shrink)

"Put together one of the world's best science writers with one of the universe's most fascinating subjects and you are bound to produce a wonderful book.... The subject of complexity is vital and controversial. This book is important and beautifully done."--Stephen Jay Gould "[Complexity] is that curious mix of complication and organization that we find throughout the natural and human worlds: the workings of a cell, the structure of the brain, the behavior of the stock market, the shifts (...) of political power.... It is time science... thinks about meaning as well as counting information.... This is the core of the complexity manifesto. Read it, think about it... but don't ignore it."--Ian Stewart, "Nature" This second edition has been brought up to date with an essay entitled "On the Edge in the Business World" and an interview with John Holland, author of "Emergence: From Chaos to Order.". (shrink)

In this article, we formally define and investigate the computational complexity of the definability problem for open first-order formulas with equality. Given a logic $\boldsymbol{\mathcal{L}}$, the $\boldsymbol{\mathcal{L}}$-definability problem for finite structures takes as an input a finite structure $\boldsymbol{A}$ and a target relation $T$ over the domain of $\boldsymbol{A}$ and determines whether there is a formula of $\boldsymbol{\mathcal{L}}$ whose interpretation in $\boldsymbol{A}$ coincides with $T$. We show that the complexity of this problem for open first-order formulas is coNP-complete. (...) We also investigate the parametric complexity of the problem and prove that if the size and the arity of the target relation $T$ are taken as parameters, then open definability is $\textrm{coW}[1]$-complete for every vocabulary $\tau $ with at least one, at least binary, relation. (shrink)

Since the foundation of the Santa Fe Institute, the new science of complex adaptive systems has seen extraordinary development, breaking with previous, more epistemological, trends in complexity theory. This article makes a critique of CAS as a model of the current global complexity. Its basic model, the cellular automaton, which focuses on the interactive dynamics among components, ignores the nature of any complex system as constructed by the observer/actor and is unable to explain the sociohistorical construction of the (...) agents/subjects and the social structure in which they are located, thus being unable to accurately represent the overall social complexity. (shrink)

This book is an attempt to demonstrate that the basic principles of phonological organization boil down to the interaction between the strength of nuclei as licensers of phonological structure and various non-rerankable scales of complexity occurring at different levels of phonological representation. The licensing relation between nuclei and the preceding onsets on the one hand, and governing relations between consonants, which are to a great extent determined by their internal melodic structure, allow us to view the phonological representation as (...) a self-organizing system, which is able to pr. (shrink)

The brains of higher mammals are extraordinary integrative devices. Signals from large numbers of functionally specialized groups of neurons distributed over many brain regions are integrated to generate a coherent, multimodal scene. Signals from the environment are integrated with ongoing, patterned neural activity that provides them with a meaningful context. We review recent advances in neurophysiology and neuroimaging that are beginning to reveal the neural mechanisms of integration. In addition, we discuss concepts and measures derived from information theory that lend (...) a theoretical basis to the notion of complexity as integration of information and suggest new experimental tests of these concepts. (shrink)

Alan Gibson has invited me to discuss publicly some of the issues I raised in my referee's report for History of Political Thought on his article ‘Ancients, Moderns and Americans: The Republicanism- Liberalism Debate Revisited’. I gladly accepted, not least because a dialogue on views of the American Founding is fitting both for the subject and Gibson's instructive characterization of it. The Federalist opens by identifying candid debate as a fundamental achievement for young America, giving hope that reflection and choice, (...) not just accident and force, can govern humans. Similarly, Gibson's argument that America's formative political thought comprises ‘multiple traditions’ — including Lockean liberalism, the republicanism of English opposition writings, and other influences — seems to define the Founding as not a monologue but a lively dialogue. I agree that complexity and not a single, pure strain of thought defines America's Founding, but this is not to say there are no fundamental principles for which the Founding stands. In the spirit of candid exchange, I will not discuss the many points in Dr Gibson's article with which I agree but those where one might interpret the American Founding differently or find an important dimension overlooked. (shrink)

Ecosystems, the human brain, ant colonies, and economic networks are all complex systems displaying collective behaviour, or emergence, beyond the sum of their parts. Complexity science is the systematic investigation of these emergent phenomena, and stretches across disciplines, from physics and mathematics, to biological and social sciences. This introductory textbook provides detailed coverage of this rapidly growing field, accommodating readers from a variety of backgrounds, and with varying levels of mathematical skill. Part I presents the underlying principles of (...) class='Hi'>complexity science, to ensure students have a solid understanding of the conceptual framework. The second part introduces the key mathematical tools central to complexity science, gradually developing the mathematical formalism, with more advanced material provided in boxes. A broad range of end of chapter problems and extended projects offer opportunities for homework assignments and student research projects, with solutions available to instructors online. Key terms are highlighted in bold and listed in a glossary for easy reference, while annotated reading lists offer the option for extended reading and research. (shrink)

We argue that if a different definition of sentence complexity is adopted and processing capacity is assessed in a way that is consistent with that definition, then the Caplan & Waters distinction between interpretive versus postinterpretive processing is unnecessary insofar that it applies to the thematic role assignment in relative-clause sentences.

Unexpected discoveries in nonequilibrium physics and nonlinear dynamics are changing our understanding of complex phenomena. Recent research has revealed fundamental new properties of matter in far-from-equilibrium conditions, and the prevalence of instability-where small changes in initial conditions may lead to amplified effects.

Dominant social sciences approaches to complexity suggest that awareness of complexity in late-modern society comes from various recent scientific insights. By examining today’s plant and human genomics sciences, I question this from both ends: first suggesting that typical public culture was already aware of particular salient forms of complexity, such as limits to predictive knowledge (which are often denied by scientific cultures themselves); second, showing how up-to-date genomics science expresses both complexity and its opposites, predictive determinism (...) and reductionism, as coexistent representations of nature and scientific knowledge. I suggest we can understand this self-authored epistemic confusion in modern science by avoiding ‘the usual suspects’ – fading simpler discourses left over from previous scientific times; media oversimplifications; or the need to ‘simplify’ to essentials, for ignorant publics – and looking instead at the silent imaginations of extra-scientific reference groups reflected and projectively performed in scientific discourses-practices themselves. Thus contradictions of complex scientific understandings are systematically created by science’s own embodiment of epistemic commitments influenced by commercial cultures, and by imagined publics who are important new constructed objects of institutional scientific concerns – over authority and trust. New dimensions of complexity thus come alive through paying attention to neglected tacit dimensions of science–society interrelations. (shrink)

When analyzing complex longitudinal data, especially data from different educational settings, researchers generally focus only on the mean part (i.e., the regression coefficients), ignoring the equally important random part (i.e., the random effect variances) of the model. By using Project English Language and Literacy Acquisition (ELLA) data, we demonstrated the importance of taking the complex data structure into account by carefully specifying the random part of the model, showing that not only can it affect the variance estimates, the standard errors, (...) and the tests of significance of the regression coefficients, it also can offer different perspectives of the data, such as information related to the developmental process. We used xxM (Mehta, 2013), which can flexibly estimate different grade-level variances separately and the potential carryover effect from each grade factor to the later time measures. Implications of the findings and limitations of the study are discussed. (shrink)

Unraveling the complex notion of “self” and “other” necessitates a layered approach that explores biology, namely genetics; philosophy, namely event phenomenology; and culture, namely religion. This essay examines (1) the latest paradigm shift occurring in the genetic sciences due to the increased knowledge of epigenetic effects on gene expression and how our DNA functions in concert with the cellular apparatus, the body, and the environment; (2) the incorporation of relationality into a philosophical understanding of self; and (3) finally, what religion (...) adds to this exploration of self. Thus, providing a glimpse at how these different approaches to identity help us understand the “self.”. (shrink)

The consensus among evolutionists seems to be that the morphological complexity of organisms increases in evolution, although almost no empirical evidence for such a trend exists. Most studies of complexity have been theoretical, and the few empirical studies have not, with the exception of certain recent ones, been especially rigorous; reviews are presented of both the theoretical and empirical literature. The paucity of evidence raises the question of what sustains the consensus, and a number of suggestions are offered, (...) including the possibility that certain cultural and/or perceptual biases are at work. In addition, a shift in emphasis from theoretical to empirical inquiry is recommended for the study of complexity, and guidelines for future empirical studies are proposed. (shrink)

Syntactic complexity effects have been investigated extensively with respect to comprehension . According to one prominent class of accounts , certain structures cause comprehension difficulty due to their scarcity in the language. But why are some structures less frequent than others? In two elicited-production experiments we investigated syntactic complexity effects in relative clauses and wh-questions varying in whether or not they contained non-local dependencies. In both experiments, we found reliable durational differences between subject-extracted structures and object-extracted structures : (...) Participants took longer to begin and produce object-extractions. Furthermore, participants were more likely to be disfluent in the object-extracted constructions. These results suggest that there is a cost associated with planning and uttering the more syntactically complex, object-extracted structures, and that this cost manifests in the form of longer durations and disfluencies. Although the precise nature of this cost remains to be determined, these effects provide one plausible explanation for the relative rarity of object-extractions: They are more costly to produce. (shrink)

The first-order logical theory Th $({\mathbb{N}},x + 1,F(x))$ is proved to be complete for the class ATIME-ALT $(2^{O(n)},O(n))$ when $F(x) = 2^{x}$ , and the same result holds for $F(x) = c^{x}, x^{c} (c \in {\mathbb{N}}, c \ge 2)$ , and F(x) = tower of x powers of two. The difficult part is the upper bound, which is obtained by using a bounded Ehrenfeucht–Fraïssé game.

This paper considers the computational complexity of the design of voting rules, which is formulated by simple games. We prove that it is an NP-complete problem to decide whether a given simple game is stable, or not.

I present evidence for a systematic complexity-coherence tradeoff in cognition. I show how feasible strategies for increasing cognitive complexity along three dimensions come at the expense of a heightened vulnerability to incoherence. I discuss two normative implications of the complexity-coherence tradeoff: a novel challenge to coherence-based theories of bounded rationality and a new strategy for vindicating the rationality of seemingly irrational cognitions. I also discuss how the complexity-coherence tradeoff sharpens recent descriptive challenges to dual process theories (...) of cognition. (shrink)

Computer-simulated scenarios have been part of psychological research on problem solving for more than 40 years. The shift in emphasis from simple toy problems to complex, more real-life oriented problems has been accompanied by discussions about the best ways to assess the process of solving complex problems. Psychometric issues such as reliable assessments and addressing correlations with other instruments have been in the foreground of these discussions and have left the content validity of complex problem solving in the background. In (...) this paper, we return the focus to content issues and address the important features that define complex problems. (shrink)

Computational complexity has often been ignored in the philosophy of mind, in philosophical artificial intelligence studies. The purpose of this paper is threefold. First and foremost, to show the importance of complexity rather than computability in philosophical and AI problems. Second, to rephrase the notion of computability in terms of solvability, i.e., treating computability as non-sufficient for establishing intelligence. The Church-Turing thesis is therefore revisited and rephrased in order to capture the ontological background of spatial and temporal (...) class='Hi'>complexity. Third, to emphasize ontological differences between different time complexities, which seem to provide a solid base for a better understanding of artificial intelligence in general. (shrink)

The present thesis, compatible with Darwinian theory, endeavours to provide original answers to the question of why the evolution of species leads to beings more complex than those existing before. It is based on the repetition of two main principles alleged to play a role in evolution towards complexity, i.e. "juxtaposition" and "integration". Juxtaposition is the addition of identical entities. Integration is the modification, or specialisation, of these entities, leading to entities on a higher level, which use the previous (...) entities as units. Several concrete examples of the process are given, at the genetic level (introns), at the anatomical level and at the social level. Structures where integration at one level leaves the units at a lower level in a state of relative autonomy can be describedusing the metaphor of the "mosaic", and the description can also be applied to the human brain and functioning of thought, where essential functions such as language or memory have a mosaic structure. (shrink)

Although much recent social science and humanities work has been a revolt against simplification, this volume explores the contrast between simplicity and complexity to reveal that this dichotomy, itself, is too simplistic. John Law and Annemarie Mol have gathered a distinguished panel of contributors to offer—particularly within the field of science studies—approaches to a theory of complexity, and at the same time a theoretical introduction to the topic. Indeed, they examine not only ways of relating to complexity (...) but complexity _in practice._ Individual essays study complexity from a variety of perspectives, addressing market behavior, medical interventions, aeronautical design, the governing of supranational states, ecology, roadbuilding, meteorology, the science of complexity itself, and the psychology of childhood trauma. Other topics include complex wholes in the sciences, moral complexity in seemingly amoral endeavors, and issues relating to the protection of African elephants. With a focus on such concepts as multiplicity, partial connections, and ebbs and flows, the collection includes narratives from Kenya, Great Britain, Papua New Guinea, the Netherlands, France, and the meetings of the European Commission, written by anthropologists, economists, philosophers, psychologists, sociologists, and scholars of science, technology, and society. _Contributors._ Andrew Barry, Steven D. Brown, Michel Callon, Chunglin Kwa, John Law, Nick Lee, Annemarie Mol, Marilyn Strathern, Laurent Thévenot, Charis Thompson. (shrink)

Our world is enormously sophisticated and nature's complexity is literally inexhaustible. As a result, projects to describe and explain natural science can never be completed. This volume explores the nature of complexity and considers its bearing on our world and how we manage our affairs within it.Rescher's overall lesson is that the management of our affairs within a socially, technologically, and cognitively complex environment is plagued with vast management problems and risks of mishap. In primitive societies, failure to (...) understand how things work can endanger a family or, at worst, a clan or tribe. In the modern world, man-made catastrophes on the model of Chernobyl can endanger millions, possibly even risking the totality of human life on our planet. Rescher explains "technological escalation" as a sort of arms race against nature in which scientific progress requires more powerful technology for observation and experimentation, and, conversely, scientific progress requires the continual enhancement of technology. The increasing complexity of science and technology (and, in consequence, of social systems) along with problems growing faster than solutions confront us with major management and decision problems.This study is the first of its kind. There have been many specialized studies of complexity in physics and computation theory, but no overall analysis of the phenomenon. Although Rescher offers a sobering outlook, he also believes that complexity entails mixed blessings: our imperfect knowledge provides a rationale for putting forth our best efforts. Rescher urges us to gear the conduct of life's practical affairs to the demands of a complex world. This highly readable and accessible volume will be of interest to those interested in philosophy, the philosophy of science, science policy studies, and future studies. (shrink)

In the philosophy of science, increasing attention has been given to the methodological novelties associated with the study of complex systems. However, there is little agreement on exactly what complex systems are. Although many characterizations of complex systems are available, they tend to be either impressionistic or overly formal. Formal definitions rely primarily on ideas from the study of computational complexity, but the relation between these formal ideas and the messy world of empirical phenomena is unclear. Here, I give (...) a definition of complex systems that draws on algorithmic complexity theory, but also provides a way of interpreting the formal idea in an empirical setting. I then use the definition to show that two canonical forms of scientific idealization are empirically inadequate when applied to complex systems. The inadequacy of these forms of idealization is shown to be the primary reason that complex systems require novel methods. Moreover, this demand for novel methods helps explain the rise of complex systems science as an autonomous discipline. (shrink)

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)

In this article we identify three previously unnoticed problems with flexible moral theories, i.e., theories according to which different moral rules apply when there is full compliance and when there is partial compliance. The first problem is that flexible theories are necessarily very complex, which undermines their ability to motivate and guide action. The second problem is that flexible theories allow for a troubling kind of (moral) domination: the duties an agent has depend on other agents' willingness to comply. Finally, (...) flexible theories introduce indeterminacy: it is sometimes impossible to determine which moral rules apply. When agents stand at the threshold—i.e., when a different rule would apply if a single additional act of noncompliance took place—it is impossible to determine which rule should apply. (shrink)

This monograph focuses on two major themes of current interest---those of complexity and emergence. Neither of the two concepts is, in the very nature of things, precisely defined or easily comprehended. Complexity is all around us while the sciences often analyze entities and events by making simplifications. But the fault lines in the latter get exposed over larger spans of space and time. Complexity entails emergence that involves discontinuity and novelty in the evolution of complex systems, based (...) on the appearance of distinctive spatial and temporal structures. Underlying an occurrence of emergence is an instability involving the transition from one stable regime to another, where distinct space-time scales acquire relevance across the transition. The structures on the two sides of the transition are characterized by distinct sets of state variables where, on one side of the transition, collective variables make their appearance. -/- Complexity and emergence are viewed in this book in the context of the Kantian noumenal-phenomenal divide. The noumenal reality is the repository of all the complexity that there is, while the phenomenal reality emerges from the noumenal in the process of our perception, interpretation, and inference. The noumenal exists in itself as a self-determined whole, and reveals itself to us in fragmentary patches as skewed projections that we assemble to form our phenomenal world that keeps on emerging ceaselessly. Our own biological evolution and the evolution of our phenomenal world occurs in a mutually consistent process, that can be referred to as co-evolution. -/- We seek regularities in the phenomenal world by means of our scientific theories which are often successful, but that success is fragile as, over larger spans of space and time, anomalies make their appearance, giving a lie to the simplicity and regularity previously presumed to have been unearthed. Simplicity, regularity, and harmony are only fleetingly located in the phenomenal world by means of our theories as these keep on being revised endlessly and often radically, thereby generating a mosaic of theories that becomes ever more complex, indicating a pervasive complexity of the noumenal world from which the phenomenal emerges by way of strictly limited projections. The foundational metaphysics on which this book is based tells us that reality is fundamentally complex, while tiny islands of simplicity, regularity, and harmony are embedded in it in isolated space-time domains. (shrink)

What exactly is complexity science? Two's company, three is complexity ; Disorder rules, OK? ; Chaos and all that jazz ; Mob mentality ; Getting connected -- What can complexity science do for me? Forecasting financial markets ; Tackling traffic networks and climbing the corporate ladder ; Looking for Mr./Mrs. Right ; Coping with conflict : next-generation wars and global terrorism -- Catching a cold, avoiding super-flu and curing cancer ; The mother of all complexities : our (...) nanoscale quantum world ; To infinity and beyond. (shrink)

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

Introduction -- The legal aspects -- Corporate governance and corporate performance -- Complexity and corporate governance -- Conclusion.

The world is complex, but acknowledging its complexity requires an appreciation for the many roles context plays in shaping natural phenomena. In _Unsimple Truths, _Sandra Mitchell argues that the long-standing scientific and philosophical deference to reductive explanations founded on simple universal laws, linear causal models, and predict-and-act strategies fails to accommodate the kinds of knowledge that many contemporary sciences are providing about the world. She advocates, instead, for a new understanding that represents the rich, variegated, interdependent fabric of many (...) levels and kinds of explanation that are integrated with one another to ground effective prediction and action. Mitchell draws from diverse fields including psychiatry, social insect biology, and studies of climate change to defend “integrative pluralism”—a theory of scientific practices that makes sense of how many natural and social sciences represent the multi-level, multi-component, dynamic structures they study. She explains how we must, in light of the now-acknowledged complexity and contingency of biological and social systems, revise how we conceptualize the world, how we investigate the world, and how we act in the world. Ultimately _Unsimple Truths _argues that the very idea of what should count as legitimate science itself should change. (shrink)