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)

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)

Benenson et al. provide a compelling case for treating greater investment into self-protection among females as an adaptive strategy. Here, we wish to expand their proposed adaptive explanation by placing it squarely in modern state-based and behavioural life-history theory, drawing on Veit'spathological complexityframework. This allows us to make sense of alternative “lifestyle” strategies, rather than pathologizing them.

In this paper I discuss how, given the complexity of biological systems, reliance on theoretical models in the development and testing of biological theories leads to an uncomfortable form of anti-realism. I locate the source of this discomfort in the uniqueness and hence diversity of biological phenomena, in contrast with the simplicity and uniformity of the subject matter of physics. I have argued elsewhere that the use of theoretical models creates an unresolvable tension between the explanatory strength and predictive (...) power of hypotheses, and I review this argument again here. My discussion parallels that of Nancy Cartwright, who claims that the use of ceteris paribus laws in physics creates an antagonism between truth and explanation that requires theoretical models to figure centrally in scientific explanation, thereby precluding realism. I argue instead that in biology it is the use of theoretical models that creates this conflict, and conclude that adequate biological explanation cannot rely on the modeling approach alone. Finally, I claim that if we accept the semantic view of theories, which makes theoretical models an integral part of our conception of theories, we must accept anti-realism as well. (shrink)

Many contemporary philosophers writing on punishment seek to show that much of the dispute between retributionists and utilitarians springs from a failure on the part of both parties to elucidate the concept of punishment. The writers are usually utilitarians who seek to show that what is true in the retributive theory is simply a point about the concept of punishment, and that for the rest, the morality of punishment is to be explained in terms of the utilitarian theory. Those who (...) attempt to destroy the retributive theory by reducing its element of truth to a mere conceptual point about the concept of punishment, seek to argue that the notion of being guilty of an offence is part of the concept of punishment. Against this kind of approach, I wish to consider whether a general theory of punishment is possible, and if so, what are its basic concepts—punishment, deserving of punishment, deserved, or justifiable punishment—and how they are to be elucidated. I shall be concerned to argue that much contemporary writing on punishment commits the Platonic fallacy of assuming that there is a single, core, paradigm use of ‘punishment’ which is to be found by elucidating the concept of legal punishment. (shrink)

The complexity approach to political economy suggests that radical uncertainty is a necessary feature of a complex and evolving socioeconomic landscape. Radical uncertainty raises various adaptive challenges that are likely to escalate in the coming decades under the “Fourth Industrial Revolution.” It jeopardizes the wellbeing of ordinary citizens, whose welfare prospects, job opportunities, and income stream are rendered insecure. It also renders precarious the robust implementation of universal human rights, including the right to social security. In fact, it will (...) be argued that human rights cannot be institutionally secured unless they are implemented in a “complexity aware” way that takes account of the uncertainty of the socioeconomic order. In particular, in order to better protect the dignity of rights holders, and to allow them to survive and thrive in the face of radical uncertainty, governments ought to explore various institutional alternatives to existing schemes. It will be suggested that most existing conditional welfare policies systematically fall short of complexity-aware institutional implementation to the extent that they rely on unreasonable assumptions regarding the availability of salient technocratic control over the complex socioeconomic order. Some economists and philosophers have suggested that UBI (Universal Basic Income) might be a viable way to implement the right to social security today. I propose that some of UBI’s most ethically and economically controversial features, such as unconditionality and universality, appear relatively appealing in light of the complexity perspective. In the absence of better alternatives, UBI might even be a requirement of a robust implementation of the human right to social security – a right that welfare states are already committed to on the level of ideal theory but predictably fail to respect in practice due to policy incoherence. However, open questions remain about whether UBI can be transformed from an ideal model into a pragmatic policy. (shrink)

In computational complexity theory, decision problems are divided into complexity classes based on the amount of computational resources it takes for algorithms to solve them. In theoretical computer science, it is commonly accepted that only functions for solving problems in the complexity class P, solvable by a deterministic Turing machine in polynomial time, are considered to be tractable. In cognitive science and philosophy, this tractability result has been used to argue that only functions in P can feasibly (...) work as computational models of human cognitive capacities. One interesting area of computational complexity theory is descriptive complexity, which connects the expressive strength of systems of logic with the computational complexity classes. In descriptive complexity theory, it is established that only first-order (classical) systems are connected to P, or one of its subclasses. Consequently, second-order systems of logic are considered to be computationally intractable, and may therefore seem to be unfit to model human cognitive capacities. This would be problematic when we think of the role of logic as the foundations of mathematics. In order to express many important mathematical concepts and systematically prove theorems involving them, we need to have a system of logic stronger than classical first-order logic. But if such a system is considered to be intractable, it means that the logical foundation of mathematics can be prohibitively complex for human cognition. In this paper I will argue, however, that this problem is the result of an unjustified direct use of computational complexity classes in cognitive modelling. Placing my account in the recent literature on the topic, I argue that the problem can be solved by considering computational complexity for humanly relevant problem solving algorithms and input sizes. (shrink)

For several decades now a set of researches from a wide range of different sectors has been developed which goes by the name of “science of complexity” and is opposed point by point to the paradigm of classical science. It challenges the idea that world is “simple.” To the reductionist idea that each process is the sum of the actions of its components it opposes a holistic view. The aim of the present article is to analyze the epistemological status (...) attributed in the science of complexity to several fundamental ideas, such as those of scientific law, objectivity, and prediction. The aim is to show that the hope of superseding reductionism by means of concepts such as that of “emergence” is fallacious and that the science of complexity proposes forms of reductionism that are even more restrictive than the classical ones, particularly when it claims to unify in a single treatment problems that vary widely in nature such as physical, biological, and social problems. (shrink)

The purpose of this note is to acknowledge a gap in a previous paper, "The complexity of revision," and to provide a corrected version of the argument.

Einstein’s razor, a corollary of Ockham’s razor, is often paraphrased as follows: make everything as simple as possible, but not simpler. This rule of thumb describes the challenge that designers of a legal system face—to craft simple laws that produce desired ends, but not to pursue simplicity so far as to undermine those ends. Complexity, simplicity’s inverse, taxes cognition and increases the likelihood of suboptimal decisions. In addition, unnecessary legal complexity can drive a misallocation of human capital toward (...) comprehending and complying with legal rules and away from other productive ends. While many scholars have offered descriptive accounts or theoretical models of legal complexity, most empirical research to date has been limited to simple measures of size, such as the number of pages in a bill. No extant research rigorously applies a meaningful model to real data. As a consequence, we have no reliable means to determine whether a new bill, regulation, order, or precedent substantially effects legal complexity. In this paper, we begin to address this need by developing a proposed empirical framework for measuring relative legal complexity. This framework is based on “knowledge acquisition”, an approach at the intersection of psychology and computer science, which can take into account the structure, language, and interdependence of law. We then demonstrate the descriptive value of this framework by applying it to the U.S. Code’s Titles, scoring and ranking them by their relative complexity. We measure various features of a title including its structural size, the net flow of its intra-title citations and its linguistic entropy. Our framework is flexible, intuitive, and transparent, and we offer this approach as a first step in developing a practical methodology for assessing legal complexity. (shrink)

"_The Moment of Complexity_ is a profoundly original work. In remarkable and insightful ways, Mark Taylor traces an entirely new way to view the evolution of our culture, detailing how information theory and the scientific concept of complexity can be used to understand recent developments in the arts and humanities. This book will ultimately be seen as a classic."-John L. Casti, Santa Fe Institute, author of _Gödel: A Life of Logic, the Mind, and Mathematics_ The science of complexity (...) accounts for that inscrutable mix of chaos and order that governs our natural world. Complexity explains how networks emerge and function, how species organize into ecosystems, how stars form into galaxies, and how just a few sequences of DNA can account for so many different life forms. Recently, the idea of complexity has taken the worlds of business and politics by storm. The concept is used to account for phenomena as varied as the behavior of the stock market, the response of voting populations, and the effects of risk management. Even Disney has used complexity theory to manage crowd control at its theme parks. Given the startling development of new information technologies, we now live in a moment of unprecedented complexity, an era in which change occurs faster than our ability to comprehend it. With _The Moment of Complexity_, Mark C. Taylor offers a timely map for this unfamiliar terrain opening in our midst, unfolding an original philosophy through a remarkable synthesis of science and culture. According to Taylor, complexity is not just a breakthrough scientific concept, but the defining quality of the post-Cold War era. The flux of digital currents swirling around us, he argues, has created a new network culture with its own distinctive logic and dynamic. Drawing on resources from information theory and evolutionary biology, Taylor explains the operation of complex adaptive systems in social and cultural processes and captures a whole new zeitgeist in the making. To appreciate the significance of our emerging network culture, he claims, we need not only to understand contemporary scientific and technological transformations, but also to explore the subtle influences of art, architecture, philosophy, religion, and higher education. _The Moment of Complexity_, then, is a remarkable work of cultural analysis on a scale rarely seen today. To follow its trajectory is to learn how we arrived at this critical moment in our culture, and to know where we might head in the twenty-first century. (shrink)

The connected and acyclic components contained in a network are identified by the computation of its complexity, where complexity of a network refers to the total number of spanning trees present within. The article in hand deals with the enumeration of the complexity of various networks’ operations such as sum, product, difference K 2, n ⊖ K 2, and the conjunction of S n with K 2. All our computations have been concluded by implementation of the methods (...) of linear algebra and matrix theory. Our derivations will also be highlighted with the assistance of 3D plots at the end of this article. (shrink)

The core issue of our target article concerns how relational complexity should be assessed. We propose that assessments must be based on actual cognitive processes used in performing each step of a task. Complexity comparisons are important for the orderly interpretation of research findings. The links between relational complexity theory and several other formulations, as well as its implications for neural functioning, connectionist models, the roles of knowledge, and individual and developmental differences, are considered.

Improving the evidence in public health is an important goal for the health promotion community. With better evidence, health professionals can make better decisions to achieve effectiveness in their interventions. The relative failure of such evidence in public health is well-known, and it is due to several factors. Briefly, from an epistemological point of view, it is not easy to develop evidence-based public health because public health interventions are highly complex and indeterminate. This paper proposes an analytical explanation of the (...) complexity and indeterminacy of public health interventions in terms of 12 points. Public health interventions are considered as a causal chain constituted by three elements and two levels of evaluation. Public health interventions thus differ from clinical interventions, which comprise two causal elements and one level of evaluation. From the two levels of evaluation, we suggest a classification of evidence into four typologies: evidence of both relations; evidence of the second but not of the first relation; evidence of the first but not of the second relation; and no evidence of either relation. In addition, a grading of indeterminacy of public health interventions is introduced. This theoretical point of view could be useful for public health professionals to better define and classify the public health interventions before acting. (shrink)

Biological systems exhibit complexity at all levels of organization. It has recently been argued by Michael Behe that at the biochemical level a type of complexity exists--irreducible complexity--that cannot possibly have arisen as the result of natural, evolutionary processes and must instead be the product of (supernatural) intelligent design. Recent work on self-organizing chemical reactions calls into question Behe's analysis of the origins of biochemical complexity. His central interpretative metaphor for biochemical complexity, that of the (...) well-designed mousetrap that ceases to function if critical parts are absent, is undermined by the observation that typical biochemical systems exhibit considerable redundancy and overlap of function. Real biochemical systems, we argue, manifest redundant complexity--a characteristic result of evolutionary processes. (shrink)

Referring to a problem-oriented research mode, transdisciplinarity faces the challenge of dealing with the complexity of real-world problems in a methodologically controlled manner. As the first st...

This article aims to study the intersection between critical realism and complexity theories through the existing literature on complex systems via an engagement with Luhmann’s autopoiesis. With reference to the philosophies of substance and persistence, I build on previous critical realist scholarship and provide an explanation for what the literature has only noted as the limitations and potentials of autopoiesis for complex systems thinking and its compatibility with Critical Realism. By highlighting how Luhmann’s autopoiesis is not a trans-immanent/ perdurantist-exdurantist (...) system, I show first how a trans immanent system through the method of calibration entails a complex causation involving objects in the environment of systems and not just within their boundaries. Second, I explain how a trans-immanent system fits with CR via the Morphogenetic Régulation framework by exploring the theme of crisis in terms of the movement from inadequate to adequate understanding of objects. (shrink)

Current formal dialectical models postulate normative rules that enable discussants to conduct dialogical interactions without committing fallacies. Though the rules for conducting a dialogue are supposed to apply to interactions between actual arguers, they are without exception theoretically motivated. This creates a gap between model and reality, because dialogue participants typically leave important content-related elements implicit. Therefore, analysts cannot readily relate normative rules to actual debates in ways that will be empirically confirmable. This paper details a new, data-driven method for (...) describing discussants’ actual reply structures, wherein corpus studies serve to acknowledge the complexity of natural argumentation. Rather than refer exclusively to propositional content as an indicator of arguing pro/contra a given claim, the proposed approach to dialogue structure tracks the sequence of dialogical moves itself. This arguably improves the applicability of theoretical dialectical models to empirical data, and thus advances the study of dialogue systems. (shrink)

We study the computational complexity of the model checking problem for quantifier-free dependence logic ${(\mathcal{D})}$ formulas. We characterize three thresholds in the complexity: logarithmic space (LOGSPACE), non-deterministic logarithmic space (NL) and non-deterministic polynomial time (NP).

Reflecting on ‘human development’ theorists face conceptual confusion, borne out experientially by contemporary ecological, social, and economic crises. Since concepts create realities (i.e. justify and motivate practices), and philosophers create concepts, it is important to consider how philosophers might respond to conceptual difficulties caused by the modern era’s still influential ‘binary’ paradigm, exemplified by the law of the excluded middle, which entails a discursive split between modernism’s ultimately predictable cosmos and postmodernism’s insistence on fundamental chaos. Supposedly obliged to choose between (...) opposites, theorists are caught between the necessity and iniquity of both. This impasse sets up conditions for what Lyotard calls ‘differends,’ and constrains our power to create responsible concepts. To show that Morin’s ‘generalised complexity’ takes us beyond the modernist/postmodernist impasse, I take up his injunction to promote ‘an epistemological reversal,’ starting from the notion of ‘open system’ and moving through ‘emergence’ and ‘organization’ to ‘logical complexity.’ Our epistemological task accordingly is to establish strategies for interpreting multiple dimensions of phenomenal reality, given the irreducibly complex relation of co-implication between mutually negating opposites. I agree with Cilliers that deconstruction is exemplary in this respect, but aim to broaden the adventure by suggesting ideas for a ‘pragmatics of complexity’ involving vocabulary, concepts, strategies, metaphors, and heuristics derived also from other philosophers and psychoanalytic theorists. The difficulty of complex thought is that it must face messes ... interconnectedness among phenomena, fogginess, uncertainty, contradiction. However, we can elaborate some conceptual tools, some principles for this adventure, and we can begin to perceive the face of the new paradigm of complexity that should emerge. (Edgar Morin, On Complexity, 2008: 6). (shrink)

The SAGE Handbook of Complexity and Management will be the first substantive scholarly work to provide a map of the state of art research in the growing field ...

Following Marr’s famous three-level distinction between explanations in cognitive science, it is often accepted that focus on modeling cognitive tasks should be on the computational level rather than the algorithmic level. When it comes to mathematical problem solving, this approach suggests that the complexity of the task of solving a problem can be characterized by the computational complexity of that problem. In this paper, I argue that human cognizers use heuristic and didactic tools and thus engage in cognitive (...) processes that make their problem solving algorithms computationally suboptimal, in contrast with the optimal algorithms studied in the computational approach. Therefore, in order to accurately model the human cognitive tasks involved in mathematical problem solving, we need to expand our methodology to also include aspects relevant to the algorithmic level. This allows us to study algorithms that are cognitively optimal for human problem solvers. Since problem solving methods are not universal, I propose that they should be studied in the framework of enculturation, which can explain the expected cultural variance in the humanly optimal algorithms. While mathematical problem solving is used as the case study, the considerations in this paper concern modeling of cognitive tasks in general. (shrink)

The paper presents evidence in bacteria for the utility of Godfrey-Smith’s environmental complexity thesis, using certain kinds of signal transduction systems as proxies for cognitive/behavioral complexity. Microbiologists already accept that the number of signal transduction proteins in a bacterial genome indicates the level of ecological complexity to which the organism is subject: the more signalling proteins, the greater the complexity. Sheer numbers are not always a reliable indicator of behavioral complexity, however. The paper proposes a (...) new, ECT-based procedure for identifying, from genomic sequence and signalling repertoire, novel bacterial candidates likely to exhibit behavioral complexity in response to a complex ecological niche. (shrink)

Many of the formalisms used in Attribute Value grammar are notational variants of languages of propositional modal logic, and testing whether two Attribute Value Structures unify amounts to testing for modal satisfiability. In this paper we put this observation to work. We study the complexity of the satisfiability problem for nine modal languages which mirror different aspects of AVS description formalisms, including the ability to express re-entrancy, the ability to express generalisations, and the ability to express recursive constraints. Two (...) main techniques are used: either Kripke models with desirable properties are constructed, or modalities are used to simulate fragments of Propositional Dynamic Logic. Further possibilities for the application of modal logic in computational linguistics are noted. (shrink)

This paper investigates how social enterprises navigate through the ethical complexity of social change and extends the ethical quandaries faced by social enterprises beyond organisational boundaries. Building on the emerging literature on the ethics of SEs, I conceptualise ethics as an engagement with power relations. I develop theoretical arguments to understand the interaction between ethical predispositions of a SE and the normative structure of the social system in which it operates. I applied this conceptualisation in a hierarchical and heterogeneous (...) rural Indian context to provide insights into the moral ambiguity of ethical decision-making and suggest pathways for ethical actions. Taking a qualitative case study approach, I followed an exemplary SE’s implementation process in India. I observed ethical challenges in designing the implementation process, selecting the beneficiaries and sustaining the programme. I also identified three actions of the SE—the action of recognition, the action of reposition and the action of collaboration—and developed a transformative process model. I discuss the theoretical implications of this research for SEs and recommend a critical engagement with ethical theories to address systemic problems. (shrink)

In this article we evaluate claims that language structure adapts to sociolinguistic environment. We present the results of two typological case studies examining the effects of the number of native (=L1) speakers and the proportion of adult second language (=L2) learners on language structure. Data from more than 300 languages suggest that testing the effect of population size and proportion of adult L2 learners on features of verbal and nominal complexity produces conflicting results on different grammatical features. The results (...) show that verbal inflectional synthesis adapts to the sociolinguistic environment but the number of genders does not. The results also suggest that modeling population size together with proportion of L2 improves model fit compared to modeling them independently of one another. We thus argue that surveying population size alone may be insufficient to detect possible adaptation of linguistic structure to the sociolinguistic environment. Rather, other features, such as proportion of L2 speakers, prestige and social network density, should be studied, and if demographic numeric data are used, they should not be used in isolation but rather in competition with other sociolinguistic features. We also suggest that not all types of language structures within a given grammatical domain are equally sensitive to the effect of sociolinguistic variables, and that more exploratory studies are needed before we can arrive at a reliable set of grammatical features that may be potentially most (and least) adaptive to social structures. (shrink)

We investigate the initial segment complexity of random reals. Let K denote prefix-free Kolmogorov complexity. A natural measure of the relative randomness of two reals α and β is to compare complexity K and K. It is well-known that a real α is 1-random iff there is a constant c such that for all n, Kn−c. We ask the question, what else can be said about the initial segment complexity of random reals. Thus, we study the (...) fine behaviour of K for random α. Following work of Downey, Hirschfeldt and LaForte, we say that αK β iff there is a constant such that for all n, . We call the equivalence classes under this measure of relative randomness K-degrees. We give proofs that there is a random real α so that lim supn K−K=∞ where Ω is Chaitin's random real. One is based upon work of Solovay, and the other exploits a new idea. Further, based on this new idea, we prove there are uncountably many K-degrees of random reals by proving that μ=0. As a corollary to the proof we can prove there is no largest K-degree. Finally we prove that if n ≠ m then the initial segment complexities of the natural n- and m-random sets and Ω︀) are different. The techniques introduced in this paper have already found a number of other applications. (shrink)

This chapter explains the notions of information, communication and learning in the context of the complex adaptive systems theory, under the version proposed by M. Gell‐Mann. Within the class of such systems, it focuses attention on complex and self‐organized natural systems as analyzed by H. Atlan. The chapter describes the epistemological context and the formal definition of self‐organization according to H. Atlan, because this definition results from a re‐interpretation of the Shannonian theorem of the noisy channel by applying it to (...) a system organized into several hierarchical levels. It is gradually restore Atlan's construction of the notion of the meaning of information in a hierarchical system, by contrasting the principles of order from noise and organizational noise and by accordingly distinguishing the concepts of complexity and complication. The principle of complexity from noise, which lies at the heart of the concept of self‐organization proposed by H. Atlan. (shrink)

In this paper we argue for the contribution that deconstruction can make towards an understanding of complex systems. We begin with a description of what we mean by complexity and how Derrida’s thought illustrates a sensitivity towards the problems we face when dealing with complex systems. This is especially clear in Derrida’s deconstruction of the structuralist linguistics of Ferdinand de Saussure. We compare this critique with the work of Edgar Morin, one of the foremost thinkers of contemporary complexity (...) and argue for the possible contributions that both thinkers provide towards an understanding of complex phenomena in the world. We then move on to illustrate the particular economy of thinking we are forced to engage with when dealing with complex systems. This economy is inspired by Derrida’s deconstruction of Bataille’s general economy. This economy illustrates the fundamental nature of critique in the process of dealing with complex systems, the third concept we explore in this paper. The process of critique illustrates the necessity for both cutting apart and weaving together of economies in order to maintain the possibility for divergent ways of being in the world. We conclude with the ethical implications of dealing with complex systems and some first steps towards an ‘ethics of complexity’. (shrink)

My paper draws on examples from molecular biology, the details of which I have developed elsewhere (Rheinberger 1992, 1993, 1995, 1997). Here, I can give only a brief outline of my argument. Reduction of complexity is a prerequisite for experimental research. To make sense of the universe of living beings, the modern biologist is bound to divide his world into fragments in which parameters can be defined, quantities measured, qualities identified. Such is the nature of any "experimental system." Ontic (...) complexity has to be reduced in order to make experimental research possible. The complexity of the research object, however, is epistemically retained in the rich context of an experimental landscape, where the eruption of "volcanic systems" can change the scenery dramatically as the result of particular, unprecedented findings. (shrink)

In this paper we show that the Gupta-Belnap systems S# and S* are П12. Since Kremer has independently established that they are П12-hard, this completely settles the problem of their complexity. The above-mentioned upper bound is established through a reduction to countable revision sequences that is inspired by, and makes use of a construction of McGee.