The paper seeks to make a contribution towards a better understanding of the current global political unrest. It argues that this unrest reflects ongoing tensions between hierarchical and non-hierarchical interactions. It also argues that the opposition between hierarchical and non-hierarchical interactions is not ontological but rather is rooted in the way we approach reality and is, therefore, subject to our control. The tendency to exclude the process of construction from our frame of vision is characteristic for the view of reality (...) that is dominant in our civilization. Contemporary theoretical perspectives that include, but are not limited to, systems theory, complexity theory, theory of self-organization, emergence theory and autopoiesis have much to offer in addressing and resolving this problem. The paper outlines some general organizing principles that should be part of this solution. (shrink)

Functional localization has historically been one of the primary goals of neuroscience. There is still debate, however, about whether it is possible, and if so what kind of theories succeed at localization. I argue for a contextualist approach to localization. Most theorists assume that widespread contextual variability in function is fundamentally incompatible with functional decomposition in the brain, because contextualist accounts will fail to be generalizable and projectable. I argue that this assumption is misplaced. A properly articulated contextualism can ground (...) successful theories of localization even without positing completely generalizable accounts. Via a case study from perceptual neuroscience, I suggest that there is strong evidence for contextual variation in the function of perceptual brain areas. I then outline a version of contextualism that is empirically adequate with respect to this data, and claim that it can still distinguish brain areas from each other according to their functional properties. Finally, I claim that the view does not fail the norms for good theory in the way that anticontextualists suppose. It is true that, on a contextualist view, we will not have theories that are completely generalizable and predictive. We can, however, have successful partial generalizations that structure ongoing investigation and lead to novel functional insight, and this success is sufficient to ground the project of functional localization. (shrink)

A scientific explanatory project, part-whole explanation, and a kind of science, part-whole science are premised on identifying, investigating, and using parts and wholes. In the biological sciences, mechanistic, structuralist, and historical explanations are part-whole explanations. Each expresses different norms, explananda, and aims. Each is associated with a distinct partitioning frame for abstracting kinds of parts. These three explanatory projects can be complemented in order to provide an integrative vision of the whole system, as is shown for a detailed case study: (...) the tetrapod limb. My diagnosis of part-whole explanation in the biological sciences as well as in other domains exploring evolved, complex, and integrated systems (e.g., psychology and cognitive science) cross-cuts standard philosophical categories of explanation: causal explanation and explanation as unification. Part-whole explanation is itself one essential aspect of part-whole science. (shrink)

Methodological reductionists practice ‘wannabe reductionism’. They claim that one should pursue reductionism, but never propose how. I integrate two strains in prior work to do so. Three kinds of activities are pursued as “reductionist”. “Successional reduction” and inter-level mechanistic explanation are legitimate and powerful strategies. Eliminativism is generally ill-conceived. Specific problem-solving heuristics for constructing inter-level mechanistic explanations show why and when they can provide powerful and fruitful tools and insights, but sometimes lead to erroneous results. I show how traditional metaphysical (...) approaches fail to engage how science is done. The methods used do so, and support a pragmatic and non-eliminativist realism. (shrink)

The cumulative open-endedness of human cultures represents a major break with the social traditions of nonhuman species. As traditions are altered and the modifications retained along the cultural lineage, human populations are capable of producing complex traits that no individual could have figured out on its own. For cultures to produce increasingly complex traditions, improvements and modifications must be kept for the next generations to build upon. High-fidelity transmission would thus act as a ratchet, retaining modifications and allowing the historical (...) buildup of complex traditions. Mechanisms acting against slippage are important, of course, but cultures also need to move forward for the ratchet to retain anything important. In this article, I argue that studies of modification-generating processes and the many ways they shape cumulative culture have been overlooked. Key to a better understanding of cultural modification processes is taking seriously that cultural traditions consist of complex, hierarchically structured recipes. Taking such structures seriously and assessing the different ways they can vary in cultural design space, a novel picture for the onset of cumulative cultural evolution emerges. I argue that a possible impediment for cumulative culture in nonhuman animals may in fact reside not so much in the fidelity of their social transmission but rather in the constraints, internal and external, on their capacity to modify complex, hierarchically structured cultural recipes. (shrink)

Plant and animal species are information-processing entities of such complexity, integration, and adaptive competence that it may be scientifically fruitful to consider them intelligent. The possibility arises from the analogy between learning and evolution, and from recent developments in evolutionary science, psychology and cognitive science. Species are now described as spatiotemporally localized individuals in an expanded hierarchy of biological entities. Intentional and cognitive abilities are now ascribed to animal, human, and artificial intelligence systems that process information adaptively, and that manifest (...) problem-solving abilities. The structural and functional similarities between such systems and species are extensive, although they “are usually obscured by population-genetic metaphors that have nonetheless contributed much to our understanding of evolution.In this target article, I use Sewall Wright's notion of the “adaptive landscape” to compare the performances of evolving species to those of intelligent organisms. With regard to their adaptive achievements and the kinds of processes by which they are achieved, biological species compare very favorably to intelligent animals by virtue of interactions between populations and their environments, between ontogeny and phylogeny, and between natural, interdemic, organic, and species selection. Addressing the question of whether species are intelligent could help to refine our ideas about species, evolution, and intelligence, and could open new lines of empirical and theoretical inquiry in many disciplines. (shrink)

The book from which these sections are excerpted is concerned with the prospects for assimilating the study of human intelligence and its products to the natural sciences through the investigation of cognitive structures, understood as systems of rules and representations that can be regarded as “mental organs.” These mental structui′es serve as the vehicles for the exercise of various capacities. They develop in the mind on the basis of an innate endowment that permits the growth of rich and highly articulated (...) structures along an intrinsically determined course under the triggering and partially shaping effect of experience, which fixes parameters in an intricate system of predetermined form. It is argued that the mind is modular in character, with a diversity of cognitive structures, each with its specific properties arid principles. Knowledge of language, of the behavior of objects, and much else crucially involves these mental structures, and is thus not characterizable in terms of capacities, dispositions, or practical abilities, nor is it necessarily grounded in experience in the standard sense of this term.Various types of knowledge and modes of knowledge acquisition are discussed in these terms. Some of the properties of the language faculty are investigated. The basic cognitive relation is “knowing a grammar”; knowledge of language is derivative and, correspondingly, raises further problems. Language as commonly understood is not a unitary phenomenon but involves a number of interacting systems: the “computational” system of grammar, which provides the representations of sound and meaning that permit a rich range of expressive potential, is distinct from a conceptual system with its own properties; knowledge of language must be distinguished from knowledge of how to use a language; and the various systems that enter into the knowledge and use of language must be further analyzed into their specific subcomponents. (shrink)

Morphological EvoDevo is a field of biological inquiry in which explicit relations between evolutionary patterns and growth or morphogenetic processes are made. Historically, morphological EvoDevo results from the coming together of several traditions, notably Naturphilosophie, embryology, the study of heterochrony, and developmental constraints. A special feature binding different approaches to morphological EvoDevo is the use of formalisms and mathematical models. Here we will introduce anatomical network analysis, a new approach centered on connectivity patterns formed by anatomical parts, with its own (...) concepts and tools specifically designed for the study of morphological EvoDevo questions. Riedl’s concept of burden is tightly related to the use of anatomical networks, providing a nexus between the evolutionary patterns and the structural constraints that shape them. (shrink)

Concerns with the use of engineering approaches in biology have recently been raised. I examine two related challenges to biological research that I call the synchronic and diachronic underdetermination problem. The former refers to challenges associated with the inference of design principles underlying system capacities when the synchronic relations between lower-level processes and higher-level systems capacities are degenerate. The diachronic underdetermination problem regards the problem of reverse engineering a system where the non-linear relations between system capacities and lower-level mechanisms are (...) changing over time. Braun and Marom argue that recent insights to biological complexity leave the aim of reverse engineering hopeless - in principle as well as in practice. While I support their call for systemic approaches to capture the dynamic nature of living systems, I take issue with the conflation of reverse engineering with naïve reductionism. I clarify how the notion of design principles can be more broadly conceived and argue that reverse engineering is compatible with a dynamic view of organisms. It may even help to facilitate an integrated account that bridges the gap between mechanistic and systems approaches. (shrink)

Convincing disputes about explanatory reductionism in the philosophy of biology require a clear and precise understanding of what a reductive explanation in biology is. The central aim of this book is to provide such an account by revealing the features that determine the reductive character of a biological explanation. Chapters I-IV provide the ground, on which I can then, in Chapter V, develop my own account of explanatory reduction in biology: Chapter I reveals the meta-philosophical assumptions that underlie my analysis (...) of reduction, Chapter II introduces the previous debate about reduction in the philosophy of biology by pointing out the most crucial lessons one should learn from this debate, Chapter III critically discusses the two perspectives on explanatory reduction that have been proposed in the philosophy of biology so far, and Chapter IV clarifies in what ways the issue of reduction is entangled with the issue of explanation. In Chapter V I present my own account of explanatory reduction. My main claim is that reductive explanations in the biological sciences possess three main characteristics: they explain the behavior of a biological system S, first, exclusively in terms of factors that are located on a lower level of organization than S, second, by focusing on factors that are internal to S , and third, by describing the genuine parts of S only as “parts in isolation”. This account is ontic because it traces the reductivity of an explanation back to certain relations that exist in the world. (shrink)

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

We consider approaches to explanation within the cognitive sciences that begin with Marr's computational level or Marr's implementational level and argue that each is subject to fundamental limitations which impair their ability to provide adequate explanations of cognitive phenomena. For this reason, it is argued, explanation cannot proceed at either level without tight coupling to the algorithmic and representation level. Even at this level, however, we argue that additional constraints relating to the decomposition of the cognitive system into a set (...) of interacting subfunctions are required. Integrated cognitive architectures that permit abstract specification of the functions of components and that make contact with the neural level provide a powerful bridge for linking the algorithmic and representational level to both the computational level and the implementational level. (shrink)

This would have been a better book if Sampson had argued his main point, the usefulness of the Simonian principle as an explanation of the evolution, structure, and acquisition of language, on its own merits, instead of making it subsidiary to his attack on ‘limited-minders’ (e.g., Noam Chomsky). The energy he has spent on the attack he might then have been willing and able to employ in developing his argument at reasonable length and detail. He might then have found that (...) argument faulty, or even wrong. Underdeveloped as it is, however, his point about the Simonian principle does seem to have thepossibility of some significance in understanding the empirical issues of this book (and the dichotomy of ‘limited’ and ‘creative’ minds is certainly not one of these).What Sampson has done inMaking Sense has the appearance of science, and theoretical linguistics, and therefore it is somewhat puzzling to find the conclusions that the human mind cannot be scientifically studied (p. 10), and that theoretical linguistics is a “mirage” (p. 210). His statement that It may still seem worthwhile to some to work out the exact implications for present-day linguistic structure of the fact that languages are evolved systems, but I cannot see that there is much glamour or, indeed, much substance in this task (p. 210) would surely be surprising to a geneticist or ethologist. We hope his apparent misunderstanding on this point will not lead him to give up his profession, in which he seems willing and able to make a significant contribution.What in particular is required is a clear indication of how the Simonian principle imposes itself in the ontogenesis of language. Consider Chomsky's example of the rule for forming questions in English. For sentence (1) below, children able to deal with such examples would give (2) but not (3) as the corresponding question (Chomsky, 1975, p. 31).The man who is tall is in the room.Is the man who is tall in the room?*Is the man who tall is in the room?Now compare Sampson's evolutionary explanation for the structure-dependence of rules which is illustrated in (1)-(3): “once a behavior-pattern has become thoroughly established, it will tend to be treated as a fixed given when used as a constituent of a more complex, later-learned behavior-pattern” (p. 183). In order for this to account for Chomsky's example it would have to be the case that children learn relative clauses before they learn questions, which simply isn't true.In conclusion, we wish not to seem unaware of the problems with the position Sampson is attacking, or unaware of the sometimes dogmatic way it too has been presented. Chomsky's hypothesis of innate linguistic ideas seems, fundamentally, to derive from the claimed rapidity and uniformity of language acquisition in the face of limited and degenerate data. Chomsky appears to have been unwilling to argue these points directly or to show their relation to others, for which he has argued, for example, the implausibility of some abstract constraint's having been learned (cf. 1971, pp. 22–44; 1975, pp. 30–33; 1980, pp. 35–52). And almost from his first invoking of rationalism in support of his linguistic method, Chomsky has himself resorted to an unnecessarily polemical attack on empiricism (cf. 1965, p. 58, n. 33). The innateness issue is just not clear or simple enough to justify so much animus, or even conviction. (shrink)

The idea of levels of organization plays a central role in the philosophy of the life sciences. In this article, I first examine the explanatory goals that have motivated accounts of levels of organization. I then show that the most state-of-the-art and scientifically plausible account of levels of organization, the account of levels of mechanism proposed by Bechtel and Craver, is fundamentally problematic. Finally, I argue that the explanatory goals can be reached by adopting a deflationary approach, where levels of (...) organization give way to more well-defined and fundamental notions, such as scale and composition. (shrink)

Paper type: Conceptual perspective. Background(s): Physics, biology, epistemology Perspectives: Theory of autopoietic systems, Popperian evolutionary epistemology and the biology of cognition. Context: This paper is a contribution to developing the theories of hierarchically complex living systems and the natures of knowledge in such systems. Problem: Dissonance between the literatures of knowledge management and organization theory and my observations of the living organization led to consideration of foundation questions: What does it mean to be alive? What is knowledge? How are life (...) and knowledge related? Method: The approach is synthetic and multidisciplinary. The concept of autopoiesis (as defined by Maturana) as a definition for life, and knowledge as a product of autopoiesis are developed from first principles regarding the behavior of dynamical systems in time. Results: Autopoiesis and the construction of knowledge are inseparable aspects of physical phenomena scalable to many levels of organization (e.g., cells, multicellular organisms, organizations, social systems, etc.). The result unifies theories of epistemology, physical dynamics, life, biological evolution, knowledge and social systems. Implications: Results highlight the importance to understand autopoiesis as first defined by Maturana and Varela – as a complex physical phenomenon persisting over time. Autopoietic “self-observation” is not paradoxical. As dynamic physical processes, any internal/external activities relating to “observations” are displaced in time. The worlds living systems act on are not those observed. “Circularly closed” systems are actually open spirals along the axis of time. (shrink)

Complexity science has proliferated across academic domains in recent years. A question arises as to whether any useful sense of ‘generalized complexity ’ can be abstracted from the various versions of complexity to be found in the literature, and whether it could prove fruitful in a scientific sense. Most attempts at defining complexity center around two kinds of notions: Structural, and temporal or dynamic. Neither of these is able to provide a foundation for the intuitive or generalized notion when taken (...) separately; structure is often a derivative notion, dependent on prior notions of complexity, and dynamic notions such as entropy are often indefinable. The philosophical notion of process may throw light on the tensions and contradictions within complexity. Robustness, for instance, a key quality of complexity, is quite naturally understood within a process-theoretical framework. Understanding complexity as process also helps one align complexity science with holistically oriented predecessors such as General System Theory, while allowing for the reductionist perspective of complexity. These results, however, have the further implication that it may be futile to search for general laws of complexity, or to hope that investigations of complex objects in one domain may throw light on complexity in unrelated domains. (shrink)

Theories of cognition and theories of social practices and institutions have often each separately acknowledged the relevance of the other; but seldom have there been consistent and sustained attempts to synthesize these two areas within one explanatory framework. This is precisely what my dissertation aims to remedy. I propose that certain recent developments and themes in philosophy of mind and cognitive science, when understood in the right way, can explain the emergence and dynamics of social practices and institutions. Likewise, the (...) view I construct explains how social practices and institutions shape the character of cognition of their constituent agents. Moreover, I explain both cognitive and social agency under the single explanatory framework provided by Dynamic Systems Theory. Drawing upon the phenomenological tradition, "embodied, "extended", "embedded", "enactive", and "ecological" approaches to cognition, as well as the conceptual resources of Dynamic Systems Theory, I construct a theory of agency that sees cognitive and social agents as far-from-equilibrium, open, recursively self-maintenant dynamic systems. Depending on the specifics of concrete circumstances, such systems, which I call "Dynamic Embodied Agents", may develop and possess emergent capacities for error-detection, flexible learning, normative behavior, representation, self-reflection, various modes of pattern-recognition, a temporal sense of self, and even moral responsibility. Some such systems are also sensitive to perceived social influences ; while reciprocally constituting and causally affecting them. (shrink)

The concepts of adaptation and fitness have such an appeal that they have been used in other scientific domains, including the social sciences. One particular aspect of this theory transfer concerns the so-called fitness landscape models. At first sight, fitness landscapes visualize how an agent, of any kind, relates to its environment, how its position is conditional because of the mutual interaction with other agents, and the potential routes towards improved fitness. The allure of fitness landscapes is first and foremost (...) that it represents a complex story about adaptation and fitness in one coherent image. Different accounts of fitness landscapes in different domains in the social sciences suggest that the properties and functions of fitness landscapes are attributed rather freely. These differences are testimony of the model’s versatility. At the same time, one will notice that the different approaches can also create ambiguity about the exact meaning and role of fitness landscapes in the social sciences. This article presents an extensive literature survey of the diverging interpretations and uses of fitness landscapes in the social sciences and discusses the implications in terms of how these models inform scientific inquiry. (shrink)

Life-science phenomena are often explained by specifying the mechanisms that bring them about. The new mechanistic philosophers have done much to substantiate this claim and to provide us with a better understanding of what mechanisms are and how they explain. Although there is disagreement among current mechanists on various issues, they share a common core position and a seeming commitment to some form of scientific realism. But is such a commitment necessary? Is it the best way to go about mechanistic (...) explanation? In this article, we propose an alternative antirealist account that also fits explanatory practice in the life sciences. We pay special attention to mechanistic models, i.e. scientific models that involve a mechanism, and to the role of coherence considerations in building such models. To illustrate our points, we consider the mechanism for the action potential. 1 Introduction2 Some Core Features of Mechanistic Explanation3 Scientific Realism and Mechanistic Explanation4 Antirealist Mechanistic Explanation: The Case of the Action Potential5 Some Outstanding Issues for the Antirealist Mechanist6 Two Problems for the Realist Mechanist7 Conclusions. (shrink)

Reconstructability analysis (RA) decomposes wholes, namely data in the form either of set theoretic relations or multivariate probability distributions, into parts, namely relations or distributions involving subsets of variables. Data is modeled and compressed by variable-based decomposition, by more general state-based decomposition, or by the use of latent variables. Models, which specify the interdependencies among the variables, are selected to minimize error and complexity.

This study provides a basic introduction to agent-based modeling (ABM) as a powerful blend of classical and constructive mathematics, with a primary focus on its applicability for social science research. The typical goals of ABM social science researchers are discussed along with the culture-dish nature of their computer experiments. The applicability of ABM for science more generally is also considered, with special attention to physics. Finally, two distinct types of ABM applications are summarized in order to illustrate concretely the duality (...) of ABM: Real-world systems can not only be simulated with verisimilitude using ABM; they can also be efficiently and robustly designed and constructed on the basis of ABM principles. (shrink)

How can we explain the intentional nature of an expert’s actions, performed without immediate and conscious control, relying instead on automatic cognitive processes? How can we account for the differences and similarities with a novice’s performance of the same actions? Can a naturalist explanation of intentional expert action be in line with a philosophical concept of intentional action? Answering these and related questions in a positive sense, this dissertation develops a three-step argument. Part I considers different methods of explanations in (...) cognitive neuroscience (Bennett & Hacker’s philosophical, conceptual analysis; Marr’s three levels of explanation; Neural Correlates of Consciousness research; mechanistic explanation), defending ‘mechanistic explanation’ as a method that provides the necessary tools for integrating interdisciplinary insights into human action. Furthermore, a dynamic, explanatory mechanism allows the assessment of the impact of learning and development on expert action in a valuable way that other methods don’t. Part II continues by scrutinizing several cognitive neuroscientific theories of learning and development (neuroconstructivism; dual-processing theories; simulation theory; extended mind/cognition hypothesis), arguing for the complex interactions between different types of processing and different action representations involved in expert action performances. Moreover, according to our discussion of a particular ‘simulation theory’ these interactions can be influenced in several ways with the use of language, allowing an agent to configure a specific action representation for performance at a later stage. The results of Parts I and II are then applied in Part III to a parallel discussion of philosophical analyses of intentional action (discussing i.a. Frankfurt, Bratman, Pacherie and Ricoeur) and cognitive neuroscientific insights in it. Both approaches are found to converge in emphasizing the importance for an expert to develop stable patterns of actions that comply maximally not only with his intentions, but also with his motor expertise and with situational conditions. Consequently, his actions – automatic, or not – rely on this ‘sculpted space of actions’. (shrink)

Plant and animal species are information-processing entities of such complexity, integration, and adaptive competence that it may be scientifically fruitful to consider them intelligent. The possibility arises from the analogy between learning and evolution, and from recent developments in evolutionary science, psychology and cognitive science. Species are now described as spatiotemporally localized individuals in an expanded hierarchy of biological entities. Intentional and cognitive abilities are now ascribed to animal, human, and artificial intelligence systems that process information adaptively, and that manifest (...) problem-solving abilities. The structural and functional similarities between such systems and species are extensive, although they “are usually obscured by population-genetic metaphors that have nonetheless contributed much to our understanding of evolution.In this target article, I use Sewall Wright's notion of the “adaptive landscape” to compare the performances of evolving species to those of intelligent organisms. With regard to their adaptive achievements and the kinds of processes by which they are achieved, biological species compare very favorably to intelligent animals by virtue of interactions between populations and their environments, between ontogeny and phylogeny, and between natural, interdemic, organic, and species selection. Addressing the question of whether species are intelligent could help to refine our ideas about species, evolution, and intelligence, and could open new lines of empirical and theoretical inquiry in many disciplines. (shrink)

Darwin, Sex and Statusargues that a human sociobiology that mistakes evolutionary theory for theories of psychology and culture is wrong, as are psychologies that could never have evolved or social sciences that posit impossible psychologies. Status develops theories of human self-awareness, cognition, and cultural capacity that are compatible with evolutionary theory. Recurring themes include: the importance of sexual selection in human evolution; our species' preoccupation with self-esteem and relative standing; the individual as an active strategist, regularly revising culturally provided information; (...) and awareness as an impressionmanagement device. Culture is a somewhat structured information pool that itself evolves, often in ways that reduce the genetic fitness of its participants. (shrink)

A fundamental goal of linguistic theory is to explain how natural languages are acquired. This paper describes some recent findings on how learners acquire syntactic knowledge for which there is little, if any, decisive evidence from the environment. The first section presents several general observations about language acquisition that linguistic theory has tried to explain and discusses the thesis that certain linguistic properties are innate because they appear universally and in the absence of corresponding experience. A third diagnostic for innateness, (...) early emergence, is the focus of the second section of the paper, in which linguistic theory is tested against recent experimental evidence on children's acquisition of syntax. (shrink)