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)

Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory. In this approach, hidden unit patterns are fed back to themselves: (...) the internal representations which develop thus reflect task demands in the context of prior internal states. A set of simulations is reported which range from relatively simple problems (temporal version of XOR) to discovering syntactic/semantic features for words. The networks are able to learn interesting internal representations which incorporate task demands with memory demands: indeed, in this approach the notion of memory is inextricably bound up with task processing. These representations reveal a rich structure, which allows them to be highly context‐dependent, while also expressing generalizations across classes of items. These representations suggest a method for representing lexical categories and the type/token distinction. (shrink)

In this particularly well written volume Graeme Hirst presents a theoretically motivated foundation for semantic interpretation (conceptual analysis) by computer, and shows how this framework facilitates the resolution of both lexical and syntactic ambiguities.

This paper presents a theory of the syntactic aspects of human sentence production. An important characteristic of unprepared speech is that overt pronunciation of a sentence can be initiated before the speaker has completely worked out the meaning content he or she is going to express in that sentence. Apparently, the speaker is able to build up a syntactically coherent utterance out of a series of syntactic fragments each rendering a new part of the meaning content. This incremental, left‐to‐right mode (...) of sentence production is the central capability of the proposed Incremental Procedural Grammar (IPG). Certain other properties of spontaneous speech, as derivable from speech errors, hesitations, self‐repairs, and language pathology, are accounted for as well.The psychological plausibility thus gained by the grammar appears compatible with a satisfactory level of linguistic plausibility in that sentences receive structural descriptions which are in line with current theories of grammar. More importantly, an explanation for the existence of configurational conditions on transformations and other linguistics rules is proposed.The basic design feature of IPG which gives rise to these psychologically and linguistically desirable properties, is the “Procedures + Stack” concept. Sentences are built not by a central constructing agency which overlooks the whole process but by a team of syntactic procedures (modules) which work—in parallel—on small parts of the sentence, have only a limited overview, and whose sole communication channel is a stack.IPG covers object complement constructions, interrogatives, and word order in main and subordinate clauses. It handles unbounded dependencies, crossserial dependencies and coordination phenomena such as gapping and conjunction reduction. It is also capable of generating self‐repairs and elliptical answers to questions. IPG has been implemented as an incremental Dutch sentence generator written in LISP. (shrink)

November 28-December 1, 1994, Denver, Colorado NIPS is the longest running annual meeting devoted to Neural Information Processing Systems.