This chapter contains section titled: Introduction Emergence of the Stability‐Diversity—Complexity Debate Mathematization of Ecological Stability The End of the Consensus Contextualization and Classification of Ecological Stability Measures of Ecological Diversity and Complexity Evaluating Stability‐Diversity—Complexity Relationships Acknowledgments References Further Reading.

In a spirit of collegial support, this paper argues that Beckett and Hager’s theoretical justification and empirical exemplifications do not do full justice to the complexity of group or team learning. We firstly reaffirm our support for the theoretical argument Becket and Hager make, though expressing some reservations about Complexity Theory, to explain the taken-for-granted assumptions that learning by an individual is the paradigm case of learning and that context plays a minimal role in this process. Drawing on (...) our joint and separate work, we demonstrate that Becket and Hager’s argument is less radical than it may initially seem because it is predicated on: (i) cognitive-bounded rather than “distributed” or “extended” conception of mind; (ii) material rather than a “immaterial” conception of activity; and (iii) co-present rather than a “fractional” or “connective” conception of ontology. Despite making this critique, we conclude by making the case that we are adding further substance to Becket and Hager’s overarching argument and, in doing so, encouraging them to be more radical about how they conceptualise the complexity of learning. (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)

Introduction -- Elucidating complexity theories -- Complexity in the natural sciences -- Complexity in social theory -- Towards transdisciplinarity -- Complexity in philosophy: complexification and the limits to knowledge -- Complexity in ethics -- Earth in the anthropocene -- Complexity and climate change -- American dreams, ecological nightmares and new visions -- Complexity and sustainability: wicked problems, gordian knots and synergistic solutions -- Conclusion.

Proof complexity is a rich subject drawing on methods from logic, combinatorics, algebra and computer science. This self-contained book presents the basic concepts, classical results, current state of the art and possible future directions in the field. It stresses a view of proof complexity as a whole entity rather than a collection of various topics held together loosely by a few notions, and it favors more generalizable statements. Lower bounds for lengths of proofs, often regarded as the key (...) issue in proof complexity, are of course covered in detail. However, upper bounds are not neglected: this book also explores the relations between bounded arithmetic theories and proof systems and how they can be used to prove upper bounds on lengths of proofs and simulations among proof systems. It goes on to discuss topics that transcend specific proof systems, allowing for deeper understanding of the fundamental problems of the subject. (shrink)

In this Very Short Introduction, John H. Holland, one of the leading figures in the field, introduces the key elements and conceptual framework of complexity. From complex physical systems such as fluid flow and the difficulties of predicting weather, to complex adaptive systems such as the diverse and interdependent ecosystems of rainforests, he uses simple examples to illustrate the approach and insights provided by complexity theory.

Contemporary theories on complex adaptive systems stem from a natural science perspective. Paul Cilliers was one of the first complexity thinkers to translate the theoretical concepts into a qualitative and normative understanding of complexity. This collected volume of essays consolidates his later work. The introduction by Preiser and Woermann reflects on the significance ofhis contribution within the broader field of complex systems thinking.

The concept of complexity has become very important in theoretical biology. It is a many faceted concept and too new and ill defined to have a universally accepted meaning. This review examines the development of this concept from the point of view of its usefulness as a criteria for the study of living systems to see what it has to offer as a new approach. In particular, one definition of complexity has been put forth which has the necessary (...) precision and rigor to be considered as a useful categorization of systems, especially as it pertains to those we call living. This definition, due to Robert Rosen, has been developed in a number of works and involves some deep new concepts about the way we view systems. In particular, it focuses on the way we view the world and actually practice science through the use of the modelling relation. This mathematical object models the process by which we assign meaning to the world we perceive. By using the modelling relation, it is possible to identify the subjective nature of our practices and deal with this issue explicitly. By so doing, it becomes clear that our notion of complexity and especially its most popular manifestations, is in large part a product of the historical processes which lead to the present state of scientific epistemology. In particular, it is a reaction to the reductionist/mechanistic view of nature which can be termed the Newtonian Paradigm. This approach to epistemology has dominated for so long that its use as a model has become implicit in most of what we do in and out of science. The alternative to this approach is examined and related to the special definition of complexity given by Rosen. Some historical examples are used to emphasize the dependence of our view of what is complex in a popular sense on the ever changing state of our knowledge. The role of some popular concepts such as chaotic dynamics are examined in this context. The fields of artificial life and related areas are also viewed from the perspective of this rigorous view of complexity and found lacking. The notion that in some way life exists at the edge of chaos is examined from the perspective of the second law of thermodynamics given by Schneider and Kay. Finally, the causal elements in complex systems are explored in relation to complexity. Rosen has shown that a clear difference in causal relations exists between complex and simple systems and that this difference leads to a uniquely useful definition of what we mean by living. Rosen makes it very clear that the class of systems which are complex is a much larger class than those which we call living. For that reason, the focus of this review will be on complexity as a stepping stone towards the deeper question of what makes a system alive. (shrink)

This chapter focuses on one of the common fallacies in Western philosophy called 'complex question (CQ)'. The fallacy of the CQ appears in two varieties. The implicit form distracts an interlocutor by assuming the truth of an unproven premise and shifting the focus of the argument in an unfounded direction. While the explicit form collapses two distinct questions into a single question such that a single answer would appear to satisfy both inquiries. The possibility that an undetected CQ might lead (...) a speaker to affirm additional, unspoken premises unintentionally makes this a popular tactic in police interrogations and debate cross‐examinations. Avoiding this rhetorical trap is only possible either by rejecting the question as posed and extemporaneously clarifying the situation on one's own terms or by remaining silent. (shrink)

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.

How does the complex nature of ecological systems affect ecologists' ability to study them? This Element argues that ecological systems are complex in a rather special way: they are causally heterogeneous. The author presents an updated philosophical account with an optimistic outlook of the methods and status of ecological research.

Introduction -- The nature of a complex world -- Unpacking complexity -- Have we thought like this before? -- The complexity of complexity theories -- Complexity and the social world -- Complexity and management -- Complexity and strategy -- Complexity and international development -- Complexity and economics -- Final reflections: what we hope you take away from this book.

Containing selected papers on the fundamentals and applications of Complexity Science, this multi-disciplinary book presents new approaches for resolving complex issues that cannot be resolved using conventional mathematical or software models. Complex Systems problems can occur in a variety of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. Complexity Science problems, the science of open systems consisting of large numbers of diverse components engaged in rich interaction, can occur in (...) a variety of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. The global behaviour of these systems emerges from the interaction of constituent components and is unpredictable but not random. The key attribute of Complex Systems is the ability to self-organise and adapt to unpredictable changes in their environment. (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 the post-Apartheid era South Africa’s universities have faced serious questions about the quality of their student learning in the face of near impossible challenges. The University of Cape Town, widely seen as the country’s leading higher education institution, has shown remarkable resilience, however, in the range of initiatives it has launched to support and enhance student learning. These initiatives, designed with a common purpose, are of course intended to work together so that their effects might be compounded and realized (...) in enhanced student learning outcomes. Drawing substantially on the power of compounding (which is itself redolent of the claim made by complexity theory that relations and emergence are crucial concepts), complexity theory offers unique insights into how and why things change – and also into how and why things remain largely the same or inexorably grind towards failure. The networked initiatives undertaken by the University of Cape Town constitute a case of learning refurbishment that is also well explained and understood in terms of complexity theory. This paper draws on concepts from complexity theory both to understand how learning might be enhanced in higher education institutions in severely straitened circumstances and to offer insights for education leaders and policy-makers in this domain. (shrink)

Computational complexity theory is a subfield of computer science originating in computability theory and the study of algorithms for solving practical mathematical problems. Amongst its aims is classifying problems by their degree of difficulty — i.e., how hard they are to solve computationally. This paper highlights the significance of complexity theory relative to questions traditionally asked by philosophers of mathematics while also attempting to isolate some new ones — e.g., about the notion of feasibility in mathematics, the $\mathbf{P} (...) \neq \mathbf{NP}$ problem and why it has proven hard to resolve, and the role of non-classical modes of computation and proof. (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)

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)

Complexity and Postmodernism explores the notion of complexity in the light of contemporary perspectives from philosophy and science. The book integrates insights from complexity and computational theory with the philosophical position of thinkers including Derrida and Lyotard. Paul Cilliers takes a critical stance towards the use of the analytical method as a tool to cope with complexity, and he rejects Searle's superficial contribution to the debate.

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)

Our socio-economic innovation ecosystem is riddled with ever-increasing complexity, as we are faced with more frequent and intense shocks, such as COVID-19. Unfortunately, addressing complexity requires a different kind of economic governance. There is increasing pressure on economics to not only going beyond its traditional mainstream boundaries but also to tackle real-world problems such as fostering structural change, enhancing sustained growth, promoting inclusive development in the era of the digital economy, and boosting green growth, while addressing the divide (...) between the financial sector and the real economy. This book demonstrates how to apply complexity science to economics, in an effective and instructive way, in the interest of life-enhancing policies. The book revolves around the non-negligible problem of why economics, to date, seems to be insufficient in guiding economic governance to navigate through real and ever-intensifying complex socio-economic and environmental challenges. With its interdisciplinary approach, the book scans the nuanced nexus between complexity and economics by incorporating, as well as transcending the state-of-the-art literature. It identifies ways to trigger opportunities for behaviour change in the economic profession with respect to how to teach and what, introducing and developing further complexity economics thinking with the configuration of its main principles and outlining the silhouette of next-generation economic governance. The book deciphers recommendations both for economic theory, practice, and education and economic governance. It will be of interest to students, scholars, academics, think tank researchers and economic policy practitioners at the national and/or supranational level. Olivér Kovács is a senior research fellow in the Department of Economics and International Economics at the University of Public Service, Budapest, Hungary. (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)

This book provides a short, hands-on introduction to the science of complexity using simple computational models of natural complex systems--with models and exercises drawn from physics, chemistry, geology, and biology. By working through the models and engaging in additional computational explorations suggested at the end of each chapter, readers very quickly develop an understanding of how complex structures and behaviors can emerge in natural phenomena as diverse as avalanches, forest fires, earthquakes, chemical reactions, animal flocks, and epidemic diseases. Natural (...) Complexity provides the necessary topical background, complete source codes in Python, and detailed explanations for all computational models. (shrink)

This volume is both a state-of-the-art display of current thinking on second language development as a complex system. It is also a tribute to Diane Larsen-Freeman for her decades of intellectual leadership in the academic disciplines of applied linguistics and second language acquisition. The chapters therein range from theoretical expositions to methodological analyses, pedagogical proposals, and conceptual frameworks for future research. In a balanced and in-depth manner, the authors provide a comprehensive and interdisciplinary understanding of second language development, with a (...) wealth of insights that promise to break the status-quo of current research and take it to exciting new territory. The book will appeal to both seasoned and novice researchers in applied linguistics, second language acquisition, bilingualism, cognitive psychology, and education, as well as to practitioners in second or foreign language teaching of any language. (shrink)

This Special Issue addresses a range of educational issues linked to main themes from our 2019 book The Emergence of Complexity: Rethinking Education as a Social Science. This book elaborated two major theses that raise fundamental questions for philosophy of education. First, that learning by groups is typically a distinctive kind of learning that is not reducible to learning by individuals. Second, that a degree of holism, as against a focus on individuals, is essential for achieving a convincing understanding (...) of this distinctive type of group learning. These two theses are of direct interest to philosophy of education since they challenges the resources of received theories of learning. Yet this kind of group learning characterises the vast bulk of human learning situations that occur outside of formal education systems. In this Special Issue introductory article we, firstly, introduce some basic principles of complexity theory, and demonstrate that, together with the concept of a ‘co-present group’ (between 2 and about 12 individuals), these ideas offer develop novel understandings of the distinctive learning that occurs within such groups. Secondly, we outline and illustrate with further examples the main features of co-present groups. Thirdly, we consolidate our conceptual work by showing five ways in which our account of group learning serves to refurbish the concept of ‘learning’. (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 this Very Short Introduction, John H. Holland, one of the leading figures in the field, introduces the key elements and conceptual framework of complexity. From complex physical systems such as fluid flow and the difficulties of predicting weather, to complex adaptive systems such as the diverse and interdependent ecosystems of rainforests, he uses simple examples to illustrate the approach and insights provided by complexity theory.

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 past 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)

Given any simply consistent formal theory F of the state complexity L(S) of finite binary sequences S as computed by 3-tape-symbol Turing machines, there exists a natural number L(F ) such that L(S) > n is provable in F only if n L(F ). The proof resembles Berry’s..

Changescapes - an introduction -- Aqueous aesthetics -- The rise of multimedia systems -- Complex dynamics disciplines -- The known world -- Attunement and agility -- Camouflage and changefulness -- Narrative hunger - geographical information systems, google street view and the colonial prospectus -- Wayfaring strangers: artistic investigations of the mood of dark tourism in online mapping -- Ghosts of a better tomorrow: the volatile formalism of 1980s film workshop productions in Hong Kong -- Cast against type -- What the (...) eye can hear -- A forest. A clearing. -- Motility -- Deep water time. (shrink)

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.

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)

This article introduces and defends the “pathological complexity thesis” as a hypothesis about the evolutionary origins of minimal consciousness, or sentience, that connects the study of animal consciousness closely with work in behavioral ecology and evolutionary biology. I argue that consciousness is an adaptive solution to a design problem that led to the extinction of complex multicellular animal life following the Avalon explosion and that was subsequently solved during the Cambrian explosion. This is the economic trade-off problem of having (...) to deal with a complex body with high degrees of freedom, what I call “pathological complexity.” By modeling the explosion of this computational complexity using the resources of state-based behavioral and life history theory we will be able to provide an evolutionary bottom-up framework to make sense of subjective experience and its function in nature by paying close attention to the ecological lifestyles of different animals. (shrink)

This chapter draws on insights from non-equilibrium thermodynamics to demonstrate the ontological inadequacy of the machine conception of the organism. The thermodynamic character of living systems underlies the importance of metabolism and calls for the adoption of a processual view, exemplified by the Heraclitean metaphor of the stream of life. This alternative conception is explored in its various historical formulations and the extent to which it captures the nature of living systems is examined. Following this, the chapter considers the metaphysical (...) implications of reconceptualizing the organism from complex machine to flowing stream. What do we learn when we reject the mechanical and embrace the processual? Three key lessons for biological ontology are identified. The first is that activity is a necessary condition for existence. The second is that persistence is grounded in the continuous self-maintenance of form. And the third is that order does not entail design. (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)

Quelque chose a changé dans notre rapport aux animaux. La " cause animale " est à l'ordre du jour, et le vivant humain est désormais plus essentiellement animal qu'humain. Cela s'appelle un zoocentrisme : au centre de notre humanité, l'animalité. En apparence, nous avons tout à gagner à cette nouvelle image de l'homme. Elle nous vient de la biologie de l'évolution, qui nous a situés, quelque part dans l'ordre des primates, en bonne compagnie avec nos cousins les grands singes. Elle (...) est aussi un appel à réformer et à moraliser nos relations avec les animaux que nous exploitons : on respecte d'autant mieux qui nous ressemble. Enfin l'animalité humaine fait de nous des esprits forts, qui ont su en finir avec les dualismes et les grands partages métaphysiques d'antan. Bref : c'est à tous égards une pensée progressiste, car ouverte à la science, généreuse envers les animaux, et philosophiquement éclairée. Il se pourrait pourtant que ces raisons d'en finir avec la différence homme-animal ne soient qu'un ensemble de pensées bancales qui, entre oubli des sciences humaines, réduction de la vie humaine à sa seule vulnérabilité et déni de ce que nous vivons en première personne, composent finalement le portrait idéologique d'un progressisme stérile. Pouvons-nous échapper au " complexe des trois singes ", ces trois façons de méconnaître ce que nous vivons et faisons comme vivants humains? Et pouvons-nous imaginer un progressisme de vérité conscient de tout ce que nous devons aux animaux sans pour autant renier ce que nous sommes? Etienne Bimbenet est professeur de philosophie contemporaine à l'université Bordeaux Montaigne. Il est notamment l'auteur de L'Animal que je ne suis plus (Gallimard, 2011), et de L'Invention du réalisme (Cerf, 2015). (shrink)

Abstracts of each chapter may be found by typing in your browser search bar, "Jeremy Horne, Managing Complexity Through Social Intelligence: Foundations of the Modern Organic Corporatist State", going to the Springer Publishing website and reading the abstracts for each chapter.

Standard semantic theories predict that non-deictic readings for complex demonstratives should be much more widely available than they in fact are. If such readings are the result of a lexical ambiguity, as Kaplan (1977) and others suggest, we should expect them to be available wherever a definite description can be used. The same prediction follows from ‘hidden argument’ theories like the ones described by King (2001) and Elbourne (2005). Wolter (2006), however, has shown that complex demonstratives admit non-deictic interpretations only (...) when a precise set of structural constrains are met. In this paper, I argue that Wolter’s results, properly understood, upend the philosophical status quo. They fatally undermine the ambiguity theory and demand a fundamental rethinking of the hidden argument approach. (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)