William Heinemann Ltd., London

This paper examines in detail the history of a set of network-structured formalisms for knowledge representation - the so-called semantic networks. While these nets have for the most part retained their basic associative nature, their primitive representational elements have differed significantly from one project to the next. These differences in underlying primitives are symptomatic of deeper philosophical disparities, and a set of five significantly different levels at which networks can be understood are discussed. One of these levels, the epistemological, or knowledge-structuring, level, has played an important implicit part in all previous notations, and is here made explicit in a way that allows a new type of network formalism to be specified. This new type of formalism accounts precisely for operations like individuation of description, internal concept structure in terms of roles and interrelations between them, and structured inheritance.

W'e present a formal syntax and semantics for the SNePS Semantic Network P recessing System (Shapiro 1979), based on a \leinongian theory of the intensional objects of thought (Rapaport 198Sa). Such a theory avoids possible worlds and is appropriate t or AI considered as "computational philosophy"-AI as the study of how intelligence is possible-or "computational psychology"- .ql

Semantic networks constitute one of the many attempts to capture human knowledge in an abstraction suitable for processing by computer program. While semantic nets enjoy widespread popularity, they seem never to live up to their authors' expectations of expressive power and ease of construction. This paper examines the fundamentals of network notation, in order to understand why the “formalism” has not been the panacea it was once hoped to be. We focus here on “concepts”—what net-authors think they are, and how network nodes might represent them. The simplistic view of concept nodes as representing extensional sets is examined, and found wanting in several respects.

However, in their conventional form, networks are rather clumsy constructs for the representation of quantification.

Publication 29, Institute of Linguistics, University of Stockholm.

Negotiation management, one such framework, has at its heart the application of computer models and related technology to a collaborative effort at dispute resolution. In this paradigm, negotiation is treated as a communicative and knowledge-intensive group problem-solving process. Easily accessible techniques are being developed for modeling both the process and substance of negotiation. In addition, tools are being designed for negotiators to use in risk and decision analysis, optimization, and precedent analysis. This paper outlines a synthesis of these elements in an integrated computer environment for negotiation management.

David E. Rumelhart Donald A. Norman Department of Psychology University of California, San Diego La Jolla, California 92037 Abstract A general system to simulate human cognitive processes is described. The four-part system comprises a nodespace to store the network structure; a supervisor; a transition network parser; and an interpreter. The method by which noun phrases operate and the process for the determiner "the" is presented. An analysis of verb structures illustrates how network structures can be constructed from primitive verb definitions that get at the underlying structures of particular verbs. The paper concludes with an illustration of a problem in question-asking. A Model of Human Memory We have constructed a large general simulation of human language and long-term memory on the premise that the study of the interrelationships among psychological processes will lead to more insight into human cognition and memory. The general implementation is basically complete, and a variety of users are starting to study specific psychological tasks (language understanding; children's development of language; primitive verb structure; reading; inference; game playing--Go and Gomoku; visual representation and memory; learning; and question answering). It is still too early to report on the results of the psychological investigation.. Therefore, this paper is a progress report on the system and the underlying psychological principles. The major guidelines have come from our attempts to represent long-term memory structures. We know that people rapidly forget the details about the surface structure of an experience but retain the meaning or interpretation of that experience indefinitely.

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