Abstract: The situated cognition movement has emerged in recent decades (although it has roots in psychologists working earlier in the 20^th century including Vygotsky, Bartlett, and Dewey) largely in reaction to an approach to explaining cognition that tended to ignore the context in which cognitive activities typically occur. Fodor’s (1980) account of the research strategy of methodological solipsism, according to which only representational states within the mind are viewed as playing causal roles in producing cognitive activity, is an extreme characterization of this approach. (As Keith Gunderson memorably commented when Fodor first presented this characterization, it amounts to reversing behaviorism by construing the mind as a white box in a black world). Critics as far back as the 1970s and 1980s objected to many experimental paradigms in cognitive psychology as not being ecologically valid; that is, they maintained that the findings only applied to the artificial circumstances created in the laboratory and did not generalize to real world settings (Neisser, 1976; 1987). The situated cognition movement, however, goes much further than demanding ecologically valid experiments—it insists that an agent’s cognitive activities are inherently embedded and supported by dynamic interactions with the agent’s body and features of its environment

Abstract: Cognitive science, as an interdisciplinary school of thought, may have recently moved beyond the bandwagon stage onto the throne of orthodoxy, but it does not make a favorable first impression on many people. Familiar reactions on first encounters range from revulsion to condescending dismissal--very few faces in the crowd light up with the sense of "Aha! So that's how the mind works! Of course!" Cognitive science leaves something out, it seems; moreover, what it apparently leaves out is important, even precious. Boiled down to its essence, cognitive science proclaims that in one way or another our minds are computers, and this seems so mechanistic, reductionistic, intellectualistic, dry, philistine, unbiological. It leaves out emotion, or what philosophers call qualia, or value, or mattering, or . . . the soul. It doesn't explain what minds are so much as attempt to explain minds away

Abstract:   At present, the prevailing Connectionist methodology forrepresenting rules is toimplicitly embody rules in neurally-wired networks. That is, the methodology adopts the stance that rules must either be hard-wired or trained into neural structures, rather than represented via explicit symbolic structures. Even recent attempts to implementproduction systems within connectionist networks have assumed that condition-action rules (or rule schema) are to be embodied in thestructure of individual networks. Such networks must be grown or trained over a significant span of time. However, arguments are presented herein that humanssometimes follow rules which arevery rapidly assignedexplicit internal representations, and that humans possessgeneral mechanisms capable of interpreting and following such rules. In particular, arguments are presented that thespeed with which humans are able to follow rules ofnovel structure demonstrates the existence of general-purpose rule following mechanisms. It is further argued that the existence of general-purpose rule following mechanisms strongly indicates that explicit rule following is not anisolated phenomenon, but may well be a common and important aspect of cognition. The relationship of the foregoing conclusions to Smolensky''s view of explicit rule following is also explored. The arguments presented here are pragmatic in nature, and are contrasted with thekind of arguments developed by Fodor and Pylyshyn in their recent, influential paper

Abstract:   Much of traditional AI exemplifies the explicit representation paradigm, and during the late 1980''s a heated debate arose between the classical and connectionist camps as to whether beliefs and rules receive an explicit or implicit representation in human cognition. In a recent paper, Kirsh (1990) questions the coherence of the fundamental distinction underlying this debate. He argues that our basic intuitions concerning explicit and implicit representations are not only confused but inconsistent. Ultimately, Kirsh proposes a new formulation of the distinction, based upon the criterion ofconstant time processing.The present paper examines Kirsh''s claims. It is argued that Kirsh fails to demonstrate that our usage of explicit and implicit is seriously confused or inconsistent. Furthermore, it is argued that Kirsh''s new formulation of the explicit-implicit distinction is excessively stringent, in that it banishes virtually all sentences of natural language from the realm of explicit representation. By contrast, the present paper proposes definitions for explicit and implicit which preserve most of our strong intuitions concerning straightforward uses of these terms. It is also argued that the distinction delineated here sustains the meaningfulness of the abovementioned debate between classicists and connectionists

Abstract:   Explicitness has usually been approached from two points of view, labelled by Kirsh the structural and the process view, that hold opposite assumptions to determine when information is explicit. In this paper, we offer an intermediate view that retains intuitions from both of them. We establish three conditions for explicit information that preserve a structural requirement, and a notion of explicitness as a continuous dimension. A problem with the former accounts was their disconnection with psychological work on the issue. We review studies by Karmiloff-Smith, and Shanks and St. John to show that the proposed conditions have psychological grounds. Finally, we examine the problem of explicit rules in connectionist systems in the light of our framework

Abstract: Unifying traditional cognitive science is the idea that thinking is a process of symbol manipulation, where symbols lead both a syntactic and a semantic life. The syntax of a symbol comprises those properties in virtue of which the symbol undergoes rule-dictated transformations. The semantics of a symbol constitute the symbolsÕ meaning or representational content. Thought consists in the syntactically determined manipulation of symbols, but in a way that respects their semantics. Thus, for instance, a calculating computer sensitive only to the shape of symbols might produce the symbol Ô5Õ in response to the inputs Ô2Õ, Ô+Õ, and Ô3Õ. As far as the computer is concerned, these symbols have no meaning, but because of its program it will produce outputs that, to the user, Òmake senseÓ given the meanings the user attributes to the symbols

Abstract: The self-advertising, at least, suggests that 'situated cognition' involves the most fundamental conceptual re-organization in AI and cognitive science, even appearing to deny that cognition is to be explained by mental representations. In their defence of the orthodox symbolic representational theory, A. Vera and H. Simon (1993) have rebutted many of these claims, but they overlook an important reading of situated arguments which may, after all, involve a revolutionary insight. I show that the whole debate turns on puzzles familiar from the history of philosophy and psychology and these may serve to clarify the current disputes

Abstract: Does self?knowledge help? A rationalist, presumably, thinks that it does: both that self?knowledge is possible and that, if gained through appropriate channels, it is desirable. Descartes notoriously claimed that, with appropriate methods of enquiry, each of his readers could become an expert on herself or himself. As well as the direct, first?person knowledge of self to which we are led in the Meditationes , we can also seek knowledge of our own bodies, and of the union of our minds and our bodies: the latter forms of self?knowledge are inevitably imperfect, but are no less important in guiding our conduct in the search after truth

Abstract: Are any nonhuman animals rational? What issues are we raising when we ask this question? Are there different kinds or levels of rationality, some of which fall short of full human rationality? Should any behaviour by nonhuman animals be regarded as rational? What kinds of tasks can animals successfully perform? What kinds of processes control their performance at these tasks, and do they count as rational processes? Is it useful or theoretically justified to raise questions about the rationality of animals at all? Should we be interested in whether they are rational? Why does it matter?