This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t h (...) e m a j o r d i s t i n c t i o n i s t h a t , w h i l e b o t h Connectionist and Classical architectures postulate representational mental states, the latter but not the former are committed to a symbol-level of representation, or to a ‘language of thought’: i.e., to representational states that have combinatorial syntactic and semantic structure. Several arguments for combinatorial structure in mental representations are then reviewed. These include arguments based on the ‘systematicity’ of mental representation: i.e., on the fact that cognitive capacities always exhibit certain symmetries, so that the ability to entertain a given thought implies the ability to entertain thoughts with semantically related contents. We claim that such arguments make a powerful case that mind/brain architecture is not Connectionist at the cognitive level. We then consider the possibility that Connectionism may provide an account of the neural (or ‘abstract neurological’) structures in which Classical cognitive architecture is implemented. We survey a n u m b e r o f t h e s t a n d a r d a r g u m e n t s t h a t h a v e b e e n o f f e r e d i n f a v o r o f Connectionism, and conclude that they are coherent only on this interpretation. (shrink)

What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

IT IS SHOWN IN DETAIL THAT RECENT ACCOUNTS FAIL TO DISTINGUISH BETWEEN INTENTIONALITY AND MERELY CAUSALLY DISPOSITIONAL STATES OF INORGANIC PHYSICAL OBJECTS—A QUICK ROAD TO PANPSYCHISM. THE CLEAR NEED TO MAKE SUCH A DISTINCTION GIVES DIRECTION FOR FUTURE WORK. A BEGINNING IS MADE TOWARD PROVIDING SUCH AN ACCOUNT.

Cognitive science typically postulates unconscious mental phenomena, computational or otherwise, to explain cognitive capacities. The mental phenomena in question are supposed to be inaccessible in principle to consciousness. I try to show that this is a mistake, because all unconscious intentionality must be accessible in principle to consciousness; we have no notion of intrinsic intentionality except in terms of its accessibility to consciousness. I call this claim the The argument for it proceeds in six steps. The essential point is that (...) intrinsic intentionality has aspectual shape: Our mental representations represent the world under specific aspects, and these aspectual features are essential to a mental state's being the state that it is. (shrink)

A revised translation of Heidegger's most important work.

John Searle's Speech Acts (1969) and Expression and Meaning (1979) developed a highly original and influential approach to the study of language. But behind both works lay the assumption that the philosophy of language is in the end a branch of the philosophy of the mind: speech acts are forms of human action and represent just one example of the mind's capacity to relate the human organism to the world. The present book is concerned with these biologically fundamental capacities, and, (...) though third in the sequence, in effect it provides the philosophical foundations for the other two. Intentionality is taken to be the crucial mental phenomenon, and its analysis involves wide-ranging discussions of perception, action, causation, meaning, and reference. In all these areas John Searle has original and stimulating views. He ends with a resolution of the 'mind-body' problem. (shrink)

The experience of consciousness is analyzed. First, a pre-theoretical characterization of the term "consciousness" is attempted. Second, the phenomenology of human consciousness is described. Specifically, consciousness is defined in terms of several patterns all of which consist of the coupling of pairs of opposites. Resonance between such opposites may be the key charactereristics of human consciousness. Third, the function of consciousness is considered. It is suggested that consciousness is functional in that it offers a medium in which cognition may be (...) conducted in a manner akin to action in the real world. More general theoretical ramifications having to do with the representational view of mind are also discussed. (shrink)

Abstract“Sign stimuli” elicit specific patterns of behavior when an organism's motivation is appropriate. In the toad, visually released prey-catching involves orienting toward the prey, approaching, fixating, and snapping. For these action patterns to be selected and released, the prey must be recognized and localized in space. Toads discriminate prey from nonprey by certain spatiotemporal stimulus features. The stimulus-response relations are mediated by innate releasing mechanisms (RMs) with recognition properties partly modifiable by experience. Striato-pretecto-tectal connectivity determines the RM's recognition and localization (...) properties, whereas medialpallio-thalamo-tectal circuitry makes the system sensitive to changes in internal state and to prior history of exposure to stimuli. RMs encode the diverse stimulus conditions referring to the same prey object through different combinations of “specialized” tectal neurons, involving cells selectively tuned to prey features. The prey-selective neurons express the outcome of information processing in functional units consisting of interconnected cells. Excitatory and inhibitory interactions among feature-sensitive tectal and pretectal neurons specify the perceptual operations involved in distinguishing the prey from its background, selecting its features, and discriminating it from predators. Other connections indicate stimulus location. The results of these analyses are transmitted by specialized neurons projecting from the tectum to bulbar/spinal motor systems, providing a sensorimotor interface. Specific combinations of such projective neurons – mediating feature- and space-related messages – form “command releasing systems” that activate corresponding motor pattern generators for appropriate prey-catching action patterns. (shrink)

THE PAPER IS A FOOTNOTE TO C B MARTIN AND KARL PFEIFER, "INTENTIONALITY AND THE NON-PSYCHOLOGICAL," "PHIL PHENOMENOL RES" 46 (1986) 531-554. A CHARACTERIZATION OF INTENTIONALITY NOT CONSIDERED THEREIN IS SHOWN, NONETHELESS, ALSO TO FAIL TO DISTINGUISH BETWEEN INTENTIONAL STATES AND MERELY PHYSICAL CAUSAL CAPACITIES.

In their critique of connectionist models Fodor and Pylyshyn (1988) dismiss such models as not being cognitive or psychological. Evaluating Fodor and Pylyshyn's critique requires examining what is required in characterizating models as 'cognitive'. The present discussion examines the various senses of this term. It argues the answer to the title question seems to vary with these different senses. Indeed, by one sense of the term, neither representa-tionalism nor connectionism is cognitive. General ramifications of such an appraisal are discussed and (...) alternative avenues for cognitive research are suggested. (shrink)

Cognitive science uses the notion of computational information processing to explain cognitive information processing. Some philosophers have argued that anything can be described as doing computational information processing; if so, it is a vacuous notion for explanatory purposes.An attempt is made to explicate the notions of cognitive information processing and computational information processing and to specify the relationship between them. It is demonstrated that the resulting notion of computational information processing can only be realized in a restrictive class of dynamical (...) systems called physical notational systems (after Goodman's theory of notationality), and that the systems generally appealed to by cognitive science-physical symbol systems-are indeed such systems. Furthermore, it turns out that other alternative conceptions of computational information processing, Fodor's (1975) Language of Thought and Cummins' (1989) Interpretational Semantics appeal to substantially the same restrictive class of systems. (shrink)