Analogical cognition refers to the ability to detect, process, and learn from relational similarities. The study of analogical and similarity cognition is widely considered one of the ‘success stories’ of cognitive science, exhibiting convergence across many disciplines on foundational questions. Given the centrality of analogy to mind and knowledge, it would benefit philosophers investigating topics in epistemology and the philosophies of mind and language to become familiar with empirical models of analogical cognition. The goal of this essay is to describe (...) recent empirical work on analogical cognition as well as model applications to philosophical topics. Topics to be discussed include the epistemological distinction between implicit knowledge and explicit knowledge, the debate between empiricists and nativists, the frame problem, expertise, creativity and autism, cognitive architecture, and relational knowledge. Particular attention is given to Dedre Gentner and colleague’s structure-mapping theory – the most developed and widely accepted model of analogical cognition. (shrink)

The scenario used by Dienes & Perner to show that individual representation can be implicit when property representation is explicit can be adapted to show that property representation can be implicit when individual representation is explicit. So there is no hierarchy of explicitness, contrary to their claim. There is a reading of the “implicit/explicit” distinction that does appear to exhibit an asymmetry parallel to that alleged to hold between individual and property. But this is not a distinction Dienes & Perner (...) mention, nor is it one that could be easily incorporated into their framework. (shrink)

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. (shrink)

Dienes & Perner's target article constitutes a significant advance in thinking about implicit knowledge. However, it largely neglects processing details and thus the time scale of mental states realizing propositional attitudes. Considering real-time processing raises questions about the possible brevity of implicit representation, the nature of processes that generate explicit knowledge, and the points of view from which knowledge may be represented. Understanding the propositional attitude analysis in terms of momentary mental states points the way toward answering these questions.

Dienes & Perner (D&P) link explicit knowledge of facts to predication. But predication is basically a linguistic notion. Their approach therefore makes it difficult to attribute knowledge of facts to non- language-users, such as animals. The explicit/implicit distinction, as D&P formulate it, is accordingly of little use for exploring the cognitive capacities of nonhuman primates – despite the increasing evidence for sophisticated social awareness among apes, implying mental representations of events in which participants are clearly distinguished. A revised formulation, less (...) biased toward syntax as it happens to have evolved in humans, could avoid this drawback. (shrink)

In this commentary, I focus on the difference between processes and representations and how this distinction relates to the question of what is controlled. Despite some views that task switching is a prototypical control process, the analysis concludes that task switching depends on the task goal representation and that control processes are there to prevent goal representations from disintegrating. Over time, these processes become obsolete, leaving behind a representation that automatically controls task performance. The distinction between processes and representations relates (...) to practice effects and automaticity and sheds light on what is meant by the phrase “automatic control.”. (shrink)

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. (shrink)

Possibly the most comprehensive collection of essays on Descartes' scientific writings ever published, this volume offers a detailed reassessment of his scientific work and its bearing on his philosophy. The 35 essays, written by some of the world's leading scholars, cover topics as diverse as optics, cosmology and medicine. The collection looks at Descartes' work in the sciences as an aspect of his natural-philosophical agenda and discusses: the central place of medicine in Descartes' overall project; the connections between his investigations (...) of specific psychological capacities and his ethics of self-government; and the debates and controversies into which he had his followers were drawn, and their role in shaping Cartesian natural philosophy; and other issues. Contributors: Peter Anstey, Jean-Robert Armogathe, Gordon Baker, David Behan, Annie Bitbol-Hespe;riès, Desmond Clarke, Betsy Decyk, Dennis Des Chene, Ve;ronique Fóti, Daniel Garber, Stephen Gaukroger, Peter Harrison, Gary Hatfield, Trevor McClaughlin, Peter McLaughlin, Katherine Morris, Alberto Guillermo, Timothy Reiss, Peter Schouls, John Schuster, Dennis Sepper, Peter Slezak, John Sutton, Yashiko Tomida, Klaas van Berkel, Theo Verbeek, Catherine Wilson, Celia Wolf-Devine, John Wright, John Yolton. (shrink)

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. (shrink)

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. (shrink)

The degree to which information is encoded explicitly in a representation is related to the computational cost of recovering or using the information. Knowledge that is implicit in a system need not be represented at all, even implicitly, if the cost of recovering it is prohibitive.

We discuss five kinds of representations of rationales and provide a formal account of how they can alter disputation. The formal model of disputation is derived from recent work in argument. The five kinds of rationales are compilation rationales, which can be represented without assuming domain-knowledge (such as utilities) beyond that normally required for argument. The principal thesis is that such rationales can be analyzed in a framework of argument not too different from what AI already has. The result is (...) a formal understanding of rationales, a partial taxonomy, and a foundation for computer programs that represent and reason with rationales.The five kinds of rationales are as follows: (c)ompression and (s)pecialization, which yield rules, and (d)isputation, which yields a decision. These are modeled as potentially changing the focus of the dispute. Then there are (f)it, a rationale for rules, and (r)esolution, a rationale for decisions. These cannot be modeled as simply; they force disputation to a meta-level, at least temporarily. (shrink)

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. (shrink)

The use of highly abstract mathematical frameworks is essential for building the sort of theoretical foundation for semantic integration needed to bring it to the level of a genuine engineering discipline. At the same time, much of the work that has been done by means of these frameworks assumes a certain amount of background knowledge in mathematics that a lot of people working in ontology, even at a fairly high theoretical level, lack. The major purpose of this short paper is (...) provide a (comparatively) simple model of semantic integration that remains within the friendlier confines of first-order languages and their usual classical semantics and logic. (shrink)

Coherence plays an important role in psychology. In this article, I suggest that coherence takes two main forms in humans’ cognitive system. The first belong to ‘system 1’. It relies on the degree of coherence between different representations to regulate them, without coherence being represented. By contrast other mechanisms, belonging to system 2, allow humans to represent the degree of coherence between different representations and to draw inferences from it. It is suggested that the mechanisms of explicit coherence evaluation have (...) social functions. They are used as means of epistemic vigilance—to evaluate what other people tell us. They can also be turned inwards to examine the coherence of our own beliefs. Their function is then to minimize the chances that we are perceived as being incoherent. Evidence from different domains of psychology is briefly reviewed in support of these hypotheses. (shrink)

In this response, we start from first principles, building up our theory to show more precisely what assumptions we do and do not make about the representational nature of implicit and explicit knowledge (in contrast to the target article, where we started our exposition with a description of a fully fledged representational theory of knowledge (RTK). Along the way, we indicate how our analysis does not rely on linguistic representations but it implies that implicit knowledge is causally efficacious; we discuss (...) the relationship between property structure implicitness and conceptual and nonconceptual content; then we consider the factual, fictional, and functional uses of representations and how we go from there to consciousness. Having shown how the basic theory deals with foundational criticisms, we indicate how the theory can elucidate issues that commentators raised in the particular application areas of explicitation, voluntary control, visual perception, memory, development (with discussion on infancy, theory of mind [TOM] and executive control, gestures), and finally models of learning. (shrink)

The philosophy of cognitive science has recently become one of the most exciting and fastest growing domains of philosophical inquiry and analysis. Until the early 1980s, nearly all of the models developed treated cognitive processes -- like problem solving, language comprehension, memory, and higher visual processing -- as rule-governed symbol manipulation. However, this situation has changed dramatically over the last half dozen years. In that period there has been an enormous shift of attention toward connectionist models of cognition that are (...) inspired by the network-like architecture of the brain. Because of their unique architecture and style of processing, connectionist systems are generally regarded as radically different from the more traditional symbol manipulation models. This collection was designed to provide philosophers who have been working in the area of cognitive science with a forum for expressing their views on these recent developments. Because the symbol-manipulating paradigm has been so important to the work of contemporary philosophers, many have watched the emergence of connectionism with considerable interest. The contributors take very different stands toward connectionism, but all agree that the potential exists for a radical shift in the way many philosophers think of various aspects of cognition. Exploring this potential and other philosophical dimensions of connectionist research is the aim of this volume. (shrink)

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. (shrink)

I examine whether it is possible for content relevant to a computer''s behavior to be carried without an explicit internal representation. I consider three approaches. First, an example of a chess playing computer carrying emergent content is offered from Dennett. Next I examine Cummins response to this example. Cummins says Dennett''s computer executes a rule which is inexplicitly represented. Cummins describes a process wherein a computer interprets explicit rules in its program, implements them to form a chess-playing device, then this (...) device executes the rules in a way that exhibits them inexplicitly. Though this approach is intriguing, I argue that the chess-playing device cannot exist as imagined. The processes of interpretation and implementation produce explicit representations of the content claimed to be inexplicit. Finally, the Chinese Room argument is examined and shown not to save the notion of inexplicit information. This means the strategy of attributing inexplicit content to a computer which is executing a rule, fails. (shrink)

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. (shrink)

We believe that the distinction between procedural and declarative knowledge unnecessarily confounds two issues: action-centeredness and accessibility, and can be made clearer through separating the two aspects. The work presents an integrated model of skill learning that takes into account both implicit and explicit processes and both action-centered and non-action-centered knowledge. We examine and simulate human data in the Letter Counting task. The work shows how the data may be captured using either the action-centered knowledge alone or the combined action-centered (...) and non-action-centered knowledge. The results provide a new perspective on skill learning. (shrink)

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. (shrink)

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? (shrink)