This paper surveys some recent work on realization in the philosophy of mind and the philosophy of science.

Expert Systems (ES) are as yet imperfectly defined. Their two consistently cited characteristics are domain knowledge and expert-level performance. We propose that current structural definitions are inadequate and suggest a view of ES as communication channels. We proceed to explore the factors influencing applicability of ES technology to an enterprise and the impacts that could be expected. A consequence of this view is the idea of incremental information loss on the path from the expert to the ES user. Strategies for (...) minimizing this loss derive naturally from our perspective and are evident in successful ES. (shrink)

Some recent cognitive-scientific research suggests that a considerable amount of intelligent action is generated not by the systematic activity of internal representations, but by complex interactions involving neural, bodily, and environmental factors. Following an analysis of this threat to representational explanation, we pursue an analogy between the role of genes in the production of biological form and the role of neural states in the production of behaviour, in order to develop a notion of genic representation. In both cases an appeal (...) to normal ecological context is used to balance multi-factoral, interactive causal determination against the intuition that certain aspects of the causal nexus play a special role in promoting adaptive success. Certain worries abut this vision help us to get a better grip on the concept of genic representation itself. We end with a puzzle concerning the relation between cognition and representation. (shrink)

Turing's analysis of computation is a fundamental part of the background of cognitive science. In this paper it is argued that a re‐interpretation of Turing's work is required to underpin theorizing about cognitive architecture. It is claimed that the symbol systems view of the mind, which is the conventional way of understanding how Turing's work impacts on cognitive science, is deeply flawed. There is an alternative interpretation that is more faithful to Turing's original insights, avoids the criticisms made of the (...) symbol systems approach and is compatible with the growing interest in agent‐environment interaction. It is argued that this interpretation should form the basis for theories of cognitive architecture. (shrink)

Vera & Simon (1993a) have argued that the theories and methods known as situated action or situativity theory are compatible with the assumptions and methodology of the physical symbol systems hypothesis and do not require a new approach to the study of cognition. When the central criterion of computational universality is added to the loose definition of a symbol system which Vera and Simon provide, it becomes apparent that there are important incompatibilities between the two approaches such that situativity theory (...) cannot be subsumed within the symbol systems approach. Symbol systems and situativity theoretic approaches are, and should be seen to be, competing approaches to the study of cognition. (shrink)

models of cognition are essentially incomplete because they fail to capture the temporal properties of mental processing. I present two possible interpretations of the dynamicists' argument from time and show that neither one is successful. The disagreement between dynamicists and symbolic theorists rests not on temporal considerations per se, but on differences over the multiple realizability of cognitive states and the proper explanatory goals of psychology. The negative arguments of dynamicists against symbolic models fail, and it is doubtful whether pursuing (...) dynamicists' explanatory goals will lead to a robust psychological theory. Introduction Elements of the symbolic theory Elements of dynamical systems theory The argument from time 4.1 First interpretation of the argument from time 4.2 Second interpretation of the argument from time Limits of dynamical systems theory. (shrink)

Certain of our concepts are innate, but many others are learned. Despite the plausibility of this claim, some have argued that the very idea of concept learning is incoherent. I present a conception of learning that sidesteps the arguments against the possibility of concept learning, and sketch several mechanisms that result in the generation of new primitive concepts. Given the rational considerations that motivate their deployment, I argue that these deserve to be called learning mechanisms. I conclude by replying to (...) the objections that these mechanisms cannot produce genuinely new content and cannot be part of genuinely cognitive explanations. (shrink)

Here I consider the relative merits of two recent models of explanation, James Woodward's interventionist-counterfactual model and the model model. According to the former, explanations are largely constituted by information about the consequences of counterfactual interventions. Problems arise for this approach because countless relevant interventions are possible in most cases and because it overlooks other kinds of equally relevant information. According the model model, explanations are largely constituted by cognitive models of actual mechanisms. On this approach, explanations tend not to (...) represent any of the aforementioned information explicitly but can instead be used to produce it on demand. The model model thus offers the more plausible account of the information of which we are aware when we have an explanation and of the ratiocinative process through which we derive many kinds of information that are relevant to the evaluation of explanations. (shrink)

Theories concerning the structure, or format, of mental representation should (1) be formulated in mechanistic, rather than metaphorical terms; (2) do justice to several philosophical intuitions about mental representation; and (3) explain the human capacity to predict the consequences of worldly alterations (i.e., to think before we act). The hypothesis that thinking involves the application of syntax-sensitive inference rules to syntactically structured mental representations has been said to satisfy all three conditions. An alternative hypothesis is that thinking requires the construction (...) and manipulation of the cognitive equivalent of scale models. A reading of this hypothesis is provided that satisfies condition (1) and which, even though it may not fully satisfy condition (2), turns out (in light of the frame problem) to be the only known way to satisfy condition (3). (shrink)

Critics of the computational connectionism of the last decade suggest that it shares undesirable features with earlier empiricist or associationist approaches, and with behaviourist theories of learning. To assess the accuracy of this charge the works of earlier writers are examined for the presence of such features, and brief accounts of those found are given for Herbert Spencer, William James and the learning theorists Thorndike, Pavlov and Hull. The idea that cognition depends on associative connections among large networks of neurons (...) is indeed one with precedents, although the implications of this for psychological issues have been interpreted variously — not all versions of connectionism are alike. (shrink)

Ramsey (1997) argues that connectionist representations 'do not earn their explanatory keep'. The aim of this paper is to examine the argument Ramsey gives to support that conclusion. In doing so, I identify two kinds of explanatory need—need relative to a possible explanation and need relative to a true explanation and argue that internal representations are not needed for either connectionist or nonconnectionist possible explanations but that it is quite likely that they are needed for true explanations. However, to show (...) that the latter is the case requires more than a consideration of the form of explanation involved. (shrink)

The strong version of the life-mind continuity thesis claims that mind can be understood as an enriched version of the same functional and organizational properties of life. Contrary to this view, in this paper I argue that mental phenomena offer distinctive properties, such as intentionality or representational content, that have no counterpart in the phenomenon of life, and that must be explained by appealing to a different level of functional and organizational principles. As a strategy, and following Maturana’s autopoietic theory (...) of cognition, I introduce a conceptual distinction between mind and cognition. I argue that cognition corresponds to the natural behaviour that every living being exhibits in the realization of its existence, and that, viewed in that way, cognition is a dynamic process of structural coupling that, unlike mental phenomena, involves no representational contents. On the basis of this distinction, I try to show that while life suffices for cognition, it does not suffice for mind. That is, that the strong continuity is not between life and mind but between life and cognition. (shrink)

Spatial aspects of words are associated with their canonical locations in the real world. Yet little research has tested whether spatial associations denoted in language comprehension generalize to their corresponding images. We directly tested the spatial aspects of mental imagery in picture and word processing (Experiment 1). We also tested whether spatial representations of motion words produce similar perceptual-interference effects as demonstrated by object words (Experiment 2). Findings revealed that words denoting an upward spatial location produced slower responses to targets (...) appearing at the top of the display, whereas words denoting a downward spatial location produced slower responses to targets appearing at the bottom of the display. Perceptual-interference effects did not obtain for pictures or for words lacking a spatial relation. These findings provide greater empirical support for the perceptual-symbols system theory (Barsalou, 1999, 2008). (shrink)

Marr’s celebrated contribution to cognitive science (Marr 1982, chap. 1) was the introduction of (at least) three levels of description/explanation. However, most contemporary research has relegated the distinction between levels to a rather dispensable remark. Ignoring such an important contribution comes at a price, or so we shall argue. In the present paper, first we review Marr’s main points and motivations regarding levels of explanation. Second, we examine two cases in which the distinction between levels has been neglected when considering (...) the structure of mental representations: Cummins et al.’s distinction between structural representation and encodings (Cummins in Journal of Philosophy, 93(12):591–614, 1996; Cummins et al. in Journal of Philosophical Research, 30:405–408, 2001) and Fodor’s account of iconic representation (Fodor 2008). These two cases illustrate the kind of problems in which researchers can find themselves if they overlook distinctions between levels and how easily these problems can be solved when levels are carefully examined. The analysis of these cases allows us to conclude that researchers in the cognitive sciences are well advised to avoid risks of confusion by respecting Marr’s old lesson. (shrink)

This commentary elaborates on Gray's conclusion that his neurophysiological model of consciousness might explain how consciousness arises from the brain, but does not address how consciousness evolved, affects behaviour or confers survival value. The commentary argues that such limitations apply to all neurophysiological or other third-person perspective models. To approach such questions the first-person nature of consciousness needs to be taken seriously in combination with third-person models of the brain.

A commentary on a target article by Alison Gopnik (1993) How we know our minds: the illusion of first-person knowledge of intentionality. Focusing on evidence of how children acquire a theory of mind, this commentary argues that there are internal inconsistencies in theories that both argue for the functional role of conscious experiences and the irreducibility of those experiences to third-person viewable information processing.

Cognitive architectures are unified theories of cognition that take the form of computational formalisms. They support computational models that collectively account for large numbers of empirical regularities using small numbers of computational mechanisms. Empirical coverage and parsimony are the most prominent criteria by which architectures are designed and evaluated, but they are not the only ones. This paper considers three additional criteria that have been comparatively undertheorized. (a) Successful architectures possess subjective and intersubjective meaning, making cognition comprehensible to individual cognitive (...) scientists and organizing groups of like-minded cognitive scientists into genuine communities. (b) Successful architectures provide idioms that structure the design and interpretation of computational models. (c) Successful architectures are strange: They make provocative, often disturbing, and ultimately compelling claims about human information processing that demand evaluation. (shrink)

When the various disciplines participating in cognitive science are listed, philosophy almost always gets a guernsey. Yet, a couple of years ago at the conference of the Cognitive Science Society in Boulder (USA), there was no philosophy or philosopher with any prominence on the program. When queried on this point, the organizer (one of the "superstars" of the field) claimed it was partly an accident, but partly also due to an impression among members of the committee that philosophy is basically (...) a waste of time. Philosophy, they thought, is mostly obscure bullshit that does little to help, and much to hinder, real progress in cognitive science. (shrink)

Whether perception involves the manipulation of representations is currently heavily debated. The embedded view advanced by Nico Orlandi seeks a middle passage between representationalism and radical enactivism. In this paper I argue for a non-representational take on EV. I argue that this is the best way to resolve the objections EV has received from both representationalists and non-representationalists. I analyze this debate, and distinguish four sorts of objections: the objection of the wrongfully cut middleman, the argument against explanatory exclusionism, the (...) case for scientific benefits of representations, and the charge of inconsistent ascription of representational status in EV. I argue that the middleman was never cut in EV, and is controversial to boot, otherwise equal, non-representational explanations have primacy over representational explanations, due to the lack of naturalistic grounds for representations and the unnecessarily ascribed cognitive load to the system. Further, I show that puts the cart before the horse, and the arguments on offer are viciously circular. However, the final objection, lays bare a deeper issue for EV. At the cost of giving up the middle position, however, the explanatory tools already available to EV can be shown to cover the work initially thought to require representation. I conclude that EV is best altered to be a non-representational theory of perception. (shrink)

According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive systems may well be dynamical systems, (...) and only sustained empirical research in cognitive science will determine the extent to which that is true. (shrink)