I reject the contention that an important theoretical difference exists between formal and natural languages.

Beyond the Pleasure Principle is Freud's most philosophical and speculative work, exploring profound questions of life and death, pleasure and pain. In it Freud introduces the fundamental concepts of the "repetition compulsion" and the "death drive," according to which a perverse, repetitive, self-destructive impulse opposes and even trumps the creative drive, or Eros. The work is one of Freud's most intensely debated, and raises important questions that have been discussed by philosophers and psychoanalysts since its first publication in 1920. The (...) text is presented here in a contemporary new translation by Gregory C. Richter. Appendices trace the work's antecedents and the many responses to it, including texts by Plato, Friedrich Nietzsche, Melanie Klein, Herbert Marcuse, Jacques Derrida, and Judith Butler, among many others. (shrink)

This target article presents a plausible evolutionary scenario for the emergence of the neural preconditions for language in the hominid lineage. In pleistocene primate lineages there was a paired evolutionary expansion of frontal and parietal neocortex (through certain well-documented adaptive changes associated with manipulative behaviors) resulting, in ancestral hominids, in an incipient Broca's region and in a configurationally unique junction of the parietal, occipital, and temporal lobes of the brain (the POT). On our view, the development of the POT in (...) our ancestors resulted in the neuroanatomical substrate consistent with the ability for representations in modality-neutral association cortex and, as a result of structure-imposing interaction with Broca's area, the hierarchically structured Evidence from paleoneurology and comparative primate neuroanatomy is used to argue that Homo habilis (2.5–2 million years ago) was the first hominid to have the appropriate gross neuroanatomical configuration to support conceptual structure. We thus suggest that the neural preconditions for language are met in H. habilis. Finally, we advocate a theory of language acquisition that uses conceptual structure as input to the learning procedures, thus bridging the gap between it and language. (shrink)

Chomsky proposes a reformulation of the theory of transformational generative grammar that takes recent developments in the descriptive analysis of particular ...

Noam Chomsky's book on syntactic structures is a serious attempts on the part of a linguist to construct within the tradition of scientific theory-construction ...

This book, which can be read independently, deals with more specifically linguistic problems in semantics and contains substantial original material.

Made-Up Minds addresses fundamental questions of learning and concept invention by means of an innovative computer program that is based on the cognitive ...

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)

These seven original essays commissioned in tribute to MIT Philosophy Professor Sylvain Bromberger present some of the most exciting research being conducted ...

In 1988 Fodor and Pylyshyn issued a challenge to the newly-popular connectionism: explain the systematicity of cognition without merely implementing a so-called classical architecture. Since that time quite a number of connectionist models have been put forward, either by their designers or by others, as in some measure demonstrating that the challenge can be met (e.g., Pollack, 1988, 1990; Smolensky, 1990; Chalmers, 1990; Niklasson and Sharkey, 1992; Brousse, 1993). Unfortu- nately, it has generally been unclear whether these models actually do (...) have this implication (see, for instance, the extensive philosophical debate in Smolensky, 1988; Fodor and McLaughlin, 1990; van Gelder, 1990, 1991; McLaughlin, 1993a, 1993b; Clark, 1993). Indeed, we know of no major supporter of classical orthodoxy who has felt compelled, by connectionist models and argu- ments, to concede in print that connectionists have in fact delivered a non-classical explanation of systematicity. (shrink)

Theories of language production have long been expressed as connectionist models. We outline the issues and challenges that must be addressed by connectionist models of lexical access and grammatical encoding, and review three recent models. The models illustrate the value of an interactive activation approach to lexical access in production, the need for sequential output in both phonological and grammatical encoding, and the potential for accounting for structural effects on errors and structural priming from learning.

What do people learn when they do not know that they are learning? Until recently, all of the work in the area of implicit learning focused on empirical questions and methods. In this book, Axel Cleeremans explores unintentional learning from an information-processing perspective. He introduces a theoretical framework that unifies existing data and models on implicit learning, along with a detailed computational model of human performance in sequence-learning situations.