Language is coordination. Pursuing this, the present Special Issue of Pragmatics & Cognition challenges two widely held positions. First, the papers reject the claim that language is essentially ‘symbolic’. Second, they deny that minds represent verbal patterns. Rather, language is social, individual, and contributes the feeling of thinking. Simply, it is distributed. Elucidating this claim, the opening papers report empirically-based work on the anticipatory dynamics of reading, their cognitive consequences, Shakespearean theatre, what images evoke, and insight problem-solving. Having given reasons (...) for rejecting linguistic autonomy, the papers turn to theory building. Initially, attention is given to a possible origin for semiotic cognition. Then, it is claimed that language functions by realizing values. Next, it is argued that human dynamics are co-regulated by cultural and biological symbols. Finally, in a review article, the distributed view of language is used to contrast Clark’s organism-centered cognition with what is here called ecologically extended cognition. (shrink)

If we are flexible, hybrid and unfinished creatures that tend to incorporate or at least employ technological artefacts in our cognitive lives, then the sort of technological regime we live under should shape the kinds of minds we possess and the sorts of beings we are. E-Memory consists in digital systems and services we use to record, store and access digital memory traces to augment, re-use or replace organismic systems of memory. I consider the various advantages of extended and embedded (...) approaches to cognition in making sense of E-Memory and some of the problems that debate can engender. I also explore how the different approaches imply different answers to questions such as: does our use of internet technology imply the diminishment of ourselves and our cognitive abilities? Whether or not our technologies can become actual parts of our minds, they may still influence our cognitive profile. I suggest E-Memory systems have four factors: totality, practical cognitive incorporability, autonomy and entanglement which conjointly have a novel incorporation profile and hence afford some novel cognitive possibilities. I find that thanks to the properties of totality and incorporability we can expect an increasing reliance on E-Memory. Yet the potentially highly entangled and autonomous nature of these technologie pose questions about whether they should really be counted as proper parts of our minds. (shrink)

What could someone represent that would enable her to track, at least within limits, others' perceptions, knowledge states and beliefs including false beliefs? An obvious possibility is that she might represent these very attitudes as such. It is sometimes tacitly or explicitly assumed that this is the only possible answer. However, we argue that several recent discoveries in developmental, cognitive, and comparative psychology indicate the need for other, less obvious possibilities. Our aim is to meet this need by describing the (...) construction of a minimal theory of mind. Minimal theory of mind is rich enough to explain systematic success on tasks held to be acid tests for theory of mind cognition including many false belief tasks. Yet minimal theory of mind does not require representing propositional attitudes, or any other kind of representation, as such. Minimal theory of mind may be what enables those with limited cognitive resources or little conceptual sophistication, such as infants, chimpanzees, scrub-jays and human adults under load, to track others' perceptions, knowledge states and beliefs. (shrink)

Accounts of mechanistic explanation have emphasized the importance of looking down—decomposing a mechanism into its parts and operations. Using research on visual processing as an exemplar, I illustrate how productive such research has been. But once multiple components of a mechanism have been identified, researchers also need to figure out how it is organized—they must look around and determine how to recompose the mechanism. Although researchers often begin by trying to recompose the mechanism in terms of sequential operations, they frequently (...) find that the components of a mechanism interact in complex ways involving positive and negative feedback and that the organization often exhibits highly interactive local networks linked by a few long-range connections (small-worlds organization) and power law distributions of connections. The mechanisms are themselves active systems that are perturbed by inputs but not set in motion by them. Researchers also need to look up —situate a mechanism in its context, which may be a larger mechanism that modulates its behavior. When looking down is combined with looking around and up, mechanistic research results in an integrated, multi-level perspective. (shrink)

This paper is an interpretation and defense of Richard Levins’ “The Strategy of Model Building in Population Biology,” which has been extremely influential among biologists since its publication 40 years ago. In this article, Levins confronted some of the deepest philosophical issues surrounding modeling and theory construction. By way of interpretation, I discuss each of Levins’ major philosophical themes: the problem of complexity, the brute-force approach, the existence and consequence of tradeoffs, and robustness analysis. I argue that Levins’ article is (...) concerned, at its core, with justifying the use of multiple, idealized models in population biology. (shrink)

What is the relation between coherence and truth? This paper rejects numerous answers to this question, including the following: truth is coherence; coherence is irrelevant to truth; coherence always leads to truth; coherence leads to probability, which leads to truth. I will argue that coherence of the right kind leads to at least approximate truth. The right kind is explanatory coherence, where explanation consists in describing mechanisms. We can judge that a scientific theory is progressively approximating the truth if it (...) is increasing its explanatory coherence in two key respects: broadening by explaining more phenomena and deepening by investigating layers of mechanisms. I sketch an explanation of why deepening is a good epistemic strategy and discuss the prospect of deepening knowledge in the social sciences and everyday life. (shrink)

Cognitive architectures are theories of cognition that try to capture the essential representations and mechanisms that underlie cognition. Research in cognitive architectures has gradually moved from a focus on the functional capabilities of architectures to the ability to model the details of human behavior, and, more recently, brain activity. Although there are many different architectures, they share many identical or similar mechanisms, permitting possible future convergence. In judging the quality of a particular cognitive model, it is pertinent to not just (...) judge its fit to the experimental data but also its simplicity and ability to make predictions. (shrink)

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

_ Convention_ was immediately recognized as a major contribution to the subject and its significance has remained undiminished since its first publication in 1969. Lewis analyzes social conventions as regularities in the resolution of recurring coordination problems-situations characterized by interdependent decision processes in which common interests are at stake. Conventions are contrasted with other kinds of regularity, and conventions governing systems of communication are given special attention.

After a decade of intense debate about mechanisms, there is still no consensus characterization. In this paper we argue for a characterization that applies widely to mechanisms across the sciences. We examine and defend our disagreements with the major current contenders for characterizations of mechanisms. Ultimately, we indicate that the major contenders can all sign up to our characterization.

Cognitive science normally takes the individual agent as its unit of analysis. In many human endeavors, however, the outcomes of interest are not determined entirely by the information processing properties of individuals. Nor can they be inferred from the properties of the individual agents, alone, no matter how detailed the knowledge of the properties of those individuals may be. In commercial aviation, for example, the successful completion of a flight is produced by a system that typically includes two or more (...) pilots interacting with each other and with a suite of technological devices. This article presents a theoretical framework that takes a distributed, socio‐technical system rather than an individual mind as its primary unit of analysis. This framework is explicitly cognitive in that it is concerned with how information is represented and how representations are transformed and propagated in the performance of tasks. An analysis of a memory task in the cockpit of a commercial airliner shows how the cognitive properties of such distributed systems can differ radically from the cognitive properties of the individuals who inhabit them. (shrink)

A basic claim of the embodiment framework is that all psychological processes are influenced by body morphology, sensory systems, motor systems, and emotions. As such, the framework holds the promise of providing a unifying perspective for psychological research. This article begins with a sketch of several arguments, from evolution to philosophy, as to why the embodiment framework is a good bet. These arguments are followed by a review of approaches to embodiment, including those from cognitive linguistics, perceptual symbol theory, and (...) action-based theories. Finally, examples are provided for how a unifying perspective might work for cognition (including language and memory), cognitive and social development, social psychology, neuroscience, clinical psychology, and psychology applied to education. (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)

With this manifesto, John Dupré systematically attacks the ideal of scientific unity by showing how its underlying assumptions are at odds with the central conclusions of science itself.

Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...

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 this book, Newell makes the case for unified theories by setting forth a candidate.

Argues that the key distinction between human and nonhuman social cognition consists in our complex, diverse and flexible capacities to shape each other's minds in ways that make them easier to interpret.

Argues that the key distinction between human and nonhuman social cognition consists in our complex, diverse and flexible capacities to shape each other's minds in ways that make them easier to interpret.

In the book, I argue that the mind can be explained computationally because it is itself computational—whether it engages in mental arithmetic, parses natural language, or processes the auditory signals that allow us to experience music. All these capacities arise from complex information-processing operations of the mind. By analyzing the state of the art in cognitive science, I develop an account of computational explanation used to explain the capacities in question.

one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...

Carl F. Craver investigates what we are doing when we use neuroscience to explain what's going on in the brain. When does an explanation succeed and when does it fail? Craver offers explicit standards for successful explanation of the workings of the brain, on the basis of a systematic view about what neuroscientific explanations are.

Robert Rupert argues against the view that human cognitive processes comprise elements beyond the boundary of the organism, developing a systems-based conception in place of this extended view. He also argues for a conciliatory understanding of the relation between the computational approach to cognition and the embedded and embodied views.

Brian Skyrms offers a fascinating demonstration of how fundamental signals are to our world. He uses various scientific tools to investigate how meaning and communication develop. Signals operate in networks of senders and receivers at all levels of life, transmitting and processing information. That is how humans and animals think and interact.

Approaches to explanation -- Causal and explanatory relevance -- The kairetic account of /D making -- The kairetic account of explanation -- Extending the kairetic account -- Event explanation and causal claims -- Regularity explanation -- Abstraction in regularity explanation -- Approaches to probabilistic explanation -- Kairetic explanation of frequencies -- Kairetic explanation of single outcomes -- Looking outward -- Looking inward.

Hutchins examines a set of phenomena that have fallen between the established disciplines of psychology and anthropology, bringing to light a new set of relationships between culture and cognition.

Carl Craver investigates what we are doing when we sue neuroscience to explain what's going on in the brain.

Second, this collection of cognitive programs evolved in the Pleistocene to solve the adaptive problems regularly faced by our hunter-gatherer ancestors-...

Much of a culture’s history – its knowledge, capacity, style, and mode of material engagement – is encoded and transmitted in its artifacts. Artifacts crystallize practice; they are a type of meme reservoir that people interpret though interaction. So, in a sense, artifacts transmit cognition; they help to transmit practice across generations, shaping the ways people engage and encounter their world. So runs one argument.

O’Regan and Noë’s sensorimotor approach rejects the old-fashioned view that perceptual experience in humans depends solely on the activation of internal representations. Reflecting a wealth of empirical work, for example active vision, the approach suggests that perceiving is, instead, a matter of bodily exploration of the outside environment. To this end, the approach says the perceiver must deploy knowledge of sensorimotor contingencies, the ways sense input changes with movement by the perceiver or object perceived. Clark has observed that the approach (...) faces a challenge accounting for the experience of temporal duration, since event-like properties cannot be characterised by reference to the sensory consequences of possible movements. This paper argues that the account can best be shored up by emphasising, more than Noë does, the dependence of perceptual experience, in general, on temporally extended, organismic interaction with the outside environment. The paper argues, moreover, that an ‘extensionalist’ account of temporal experience could help make sense of object experience, which is itself, plausibly, an experience of temporal duration. (shrink)

In this paper I first offer a systematic outline of a series of conceptual novelties in the life-sciences that have favoured, over the last three decades, the emergence of a more social view of biology. I focus in particular on three areas of investigation: (1) technical changes in evolutionary literature that have provoked a rethinking of the possibility of altruism, morality and prosocial behaviours in evolution; (2) changes in neuroscience, from an understanding of the brain as an isolated data processor (...) to the ultrasocial and multiply connected social brain of contemporary neuroscience; and (3) changes in molecular biology, from the view of the gene as an autonomous master of development to the ‘reactive genome’ of the new emerging field of molecular epigenetics. In the second section I reflect on the possible implications for the social sciences of this novel biosocial terrain and argue that the postgenomic language of extended epigenetic inheritance and blurring of the nature/nurture boundaries will be as provocative for neo-Darwinism as it is for the social sciences as we have known them. Signs of a new biosocial language are emerging in several social-science disciplines and this may represent an exciting theoretical novelty for twenty-first social theory. (shrink)