The notion of a ‘symbol’ plays an important role in the disciplines of Philosophy, Psychology, Computer Science, and Cognitive Science. However, there is comparatively little agreement on how this notion is to be understood, either between disciplines, or even within particular disciplines. This paper does not attempt to defend some putatively ‘correct’ version of the concept of a ‘symbol.’ Rather, some terminological conventions are suggested, some constraints are proposed and a taxonomy of the kinds of issue that give rise to (...) disagreement is articulated. The goal here is to provide something like a ‘geography’ of the various notions of ‘symbol’ that have appeared in the various literatures, so as to highlight the key issues and to permit the focusing of attention upon the important dimensions. In particular, the relationship between ‘tokens’ and ‘symbols’ is addressed. The issue of designation is discussed in some detail. The distinction between simple and complex symbols is clarified and an apparently necessary condition for a system to be potentially symbol, or token bearing, is introduced. (shrink)

Mechanistic explanation has an impressive track record of advancing our understanding of complex, hierarchically organized physical systems, particularly biological and neural systems. But not every complex system can be understood mechanistically. Psychological capacities are often understood by providing cognitive models of the systems that underlie them. I argue that these models, while superficially similar to mechanistic models, in fact have a substantially more complex relation to the real underlying system. They are typically constructed using a range of techniques for abstracting (...) the functional properties of the system, which may not coincide with its mechanistic organization. I describe these techniques and show that despite being non-mechanistic, these cognitive models can satisfy the normative constraints on good explanations. (shrink)

To explain why, in scientific problem solving, a diagram can be “worth ten thousand words,” Jill Larkin and Herbert Simon (1987) relied on a computer model: two representations can be “informationally” equivalent but differ “computationally,” just as the same data can be encoded in a computer in multiple ways, more or less suited to different kinds of processing. The roots of this proposal lay in cognitive psychology, more precisely in the “imagery debate” of the 1970s on whether there are image-like (...) mental representations. Simon (1972, 1978) hoped to solve this debate by thoroughly reducing the differences between forms of mental representations (e.g., between images and sentences) to differences in computational efficiency; to carry out this reduction, he borrowed from computer science the concepts of data type and of data structure. I argue that, in the end, his account amounted to nothing more than characterizing representations by the fast operations on them. This analysis then allows me to assess what Simon’s approach actually achieves when transported from psychology to the study of scientific representations, as in Larkin and Simon (1987): it allows comparing, not representations in and of themselves, but rather the computational roles they play in particular problem-solving processes—that is, representations together with a particular way of using them. (shrink)

In the physical sciences a rigorous theory is a hierarchy of descriptions in which causal relationships between many general types of entity at a phenomenological level can be derived from causal relationships between smaller numbers of simpler entities at more detailed levels. The hierarchy of descriptions resembles the modular hierarchy created in electronic systems in order to be able to modify a complex functionality without excessive side effects. Such a hierarchy would make it possible to establish a rigorous scientific theory (...) of consciousness. The causal relationships implicit in definitions of access consciousness and phe- nomenal consciousness are made explicit, and the corresponding causal relationships at the more detailed levels of perception, memory, and skill learning described. Extension of these causal relationships to physiological and neural levels is discussed. The general capability of a range of current consciousness models to support a modular hierarchy which could generate these causal relationships is reviewed, and the specific capabilities of two models with good general capabilities are compared in some detail. Ó 2003 Elsevier Inc. All rights reserved. (shrink)

This paper argues for an explanation of the mechanistic (computational) basis of consciousness that is based on the distinction between localist (symbolic) representation and distributed representation, the ideas of which have been put forth in the connectionist literature. A model is developed to substantiate and test this approach. The paper also explores the issue of the functional roles of consciousness, in relation to the proposed mechanistic explanation of consciousness. The model, embodying the representational difference, is able to account for the (...) functional role of consciousness, in the form of the synergy between the conscious and the unconscious. The fit between the model and various cognitive phenomena and data (documented in the psychological literatures) is discussed to accentuate the plausibility of the model and its explanation of consciousness. Comparisons with existing models of consciousness are made in the end. (shrink)

In this article, I present a substantive proposal about the timing and nature of the final stage of the evolution of full human language, the transition from so-called “protolanguage” to language, and on the origins of a simple protolanguage with structure and displaced reference; a proposal that depends on the idea that the initial expansion of communicative powers in our lineage involved a much expanded role for gesture and mime. But though it defends a substantive proposal, the article also defends (...) and illustrates a methodological proposal too. I argue that language is a special case of a more general phenomenon—cumulative cultural evolution—and while we rarely have direct information about communication, we have more direct information about the cumulative cultural evolution of technical skill, ecological strategies, and social complexity. These same factors also enable us to make a reasonable estimate of the intergenerational social learning capacities of these communities and of the communicative demands these communities face. For example, we can, at least tentatively, identify forms of cooperation that are stable only if third party information is transmitted widely, cheaply, and accurately. So we can use these more direct markers of information accumulation to locate, in broad terms, the period in our evolutionary history during which we became lingual. (shrink)

A key component of much current research in behavioral ecology, cognitive science, and economics is a model of the mind at least partly based on beliefs and desires. However, despite this prevalence, there are still many open questions concerning both the structure and the applicability of this model. This is especially so when it comes to its ‘desire’ part: in particular, it is not yet entirely clear when and why we should expect organisms to be desire-based—understood so as to imply (...) that they consult explicit tokenings of what they ought to do—as opposed to being drive-based—understood so as to imply that they react to the world using behavioral reflexes. In this paper, I present the beginnings of an answer to this question. To do this, I start by showing that an influential recent attempt to address these issues—due to Kim Sterelny—fails to be fully successful, as it does not make sufficiently clear what the relative benefits and disadvantages of drive-based and desire-based cognitive architectures are. I then present an alternative account of this matter based on the idea that organisms that can follow explicit behavioral rules avoid having to memorize a large set of state of the world–action connections—which can be adaptive. Finally, I apply this account to the question of what the cognitive value of mental representations should be seen to be; here, I conclude that—contrary to some recent claims—relying on mental representations can make decision making easier, not harder, but also that—in line with these recent claims—whether it does so depends on the details of the case. (shrink)

In this paper, I argue that a natural selection-based perspective gives reasons for thinking that the core of the ability to mindread cognitively complex mental states is subserved by a simulationist process—that is, that it relies on nonspecialised mechanisms in the attributer's cognitive architecture whose primary function is the generation of her own decisions and inferences. In more detail, I try to establish three conclusions. First, I try to make clearer what the dispute between simulationist and non-simulationist theories of mindreading (...) fundamentally is about. Second, I try to make more precise an argument that is sometimes hinted at in support of the former: this 'argument from simplicity' suggests that, since natural selection disfavours building extra cognitive systems where this can be avoided, simulationist theories of mindreading are more in line with natural selection than their competitors. As stated, though, this argument overlooks the fact that building extra cognitive systems can also yield benefits: in particular, it can allow for the parallel processing of multiple problems and it makes for the existence of backups for important elements of the organism's mind. I therefore try to make this argument more precise by investigating whether these benefits also apply to the present case—and conclude negatively. My third aim in this paper is to use this discussion of mindreading as a means for exploring the promises and difficulties of evolutionary arguments in philosophy and psychology more generally. (shrink)

According to David Chalmers, the hard problem of consciousness consists of explaining how and why qualitative experience arises from physical states. Moreover, Chalmers argues that materialist and reductive explanations of mentality are incapable of addressing the hard problem. In this chapter, I suggest that Chalmers’ hard problem can be usefully distinguished into a ‘how question’ and ‘why question,’ and I argue that evolutionary biology has the resources to address the question of why qualitative experience arises from brain states. From this (...) perspective, I discuss the different kinds of evolutionary explanations (e.g., adaptationist, exaptationist, spandrel) that can explain the origins of the qualitative aspects of various conscious states. This argument is intended to clarify which parts of Chalmers’ hard problem are amenable to scientific analysis. (shrink)

This paper aims to explore mechanistic and teleological explanations of consciousness. In terms of mechanistic explanations, it critiques various existing views, especially those embodied by existing computational cognitive models. In this regard, the paper argues in favor of the explanation based on the distinction between localist (symbolic) representation and distributed representation (as formulated in the connectionist literature), which reduces the phenomenological difference to a mechanistic difference. Furthermore, to establish a teleological explanation of consciousness, the paper discusses the issue of the (...) functional role of consciousness on the basis of the aforementioned mechanistic explanation. A proposal based on synergistic interaction between the conscious and the unconscious is advanced that encompasses various existing views concerning the functional role of consciousness. This two-step deepening explanation has some empirical support, in the form of a cognitive model and various cognitive data that it captures. © 2001 Elsevier Science B.V. All rights reserved. (shrink)

This paper investigates connectionism's potential to solve the frame problem. The frame problem arises in the context of modelling the human ability to see the relevant consequences of events in a situation. It has been claimed to be unsolvable for classical cognitive science, but easily manageable for connectionism. We will focus on a representational approach to the frame problem which advocates the use of intrinsic representations. We argue that although connectionism's distributed representations may look promising from this perspective, doubts can (...) be raised about the potential of distributed representations to allow large amounts of complexly structured information to be adequately encoded and processed. It is questionable whether connectionist models that are claimed to effectively represent structured information can be scaled up to a realistic extent. We conclude that the frame problem provides a difficulty to connectionism that is no less serious than the obstacle it constitutes for classical cognitive science. (shrink)

In this thesis, I defend the explanatory force of algorithmic information processing models in cognitive neuroscience. I describe the algorithmic approach to cognitive explanation, its relation to Shea’s theory of cognitive representation, and challenges stemming from neuronal population analysis and dimensionality reduction. I then consider competing interpretations of some neuroscientific data that have been central to the debate. I argue in favor of a sequenced computational explanation of the phenomenon, contra Burnston. Finally, I argue that insights from theoretical neuroscience allow (...) us to understand why dimensionality reduction does not militate against localizing distinct contents to distinct components of functioning brain systems. (shrink)

It is argued that a chief obstacle to a naturalistic explanation of the origins of mind is human exceptionalism, as exempli fi ed in the seventeenth century by René Descartes and in the twentieth century by Noam Chomsky. As an antidote to human exceptionalism, we turn to the account of aesthetic judgment in Charles Darwin’s Descent of Man , according to which the mental capacities of humans differ from those of lower animals only in degree, and not in kind. Thoroughgoing (...) naturalistic explanation of these capacities is made easier by shifting away from the substance-metaphysical implications of the search for an account of mind , toward a dispositional account of the origins of mindfulness . (shrink)

This paper aims at answering the question “When is informational content explicitly represented in a cognitive system?”. I first distinguish the explicitness this question is about from other kinds of explicitness that are currently investigated in philosophy of mind, and situate the components of the question within the various conceptual frameworks that are used to study mental representations. I then present and criticize, on conceptual and empirical grounds, two basic ways of answering the question, the first one coming from the (...) classical computational theory of mind, the latter one issued from a procedural conception of informational contents. I then argue for a new answer to the initial question, an answer that retains some valuable insights of the criticized theories, but which underlines the importance and the interpretational source of the distinctiveness proper to explicitly represented contents. (shrink)