Parallelization In Inference Systems
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Parallelization in Inference Systems
Author: Bertram Fronhöfer
language: en
Publisher: Springer Science & Business Media
Release Date: 1992-04-22
This volume contains the proceedings of an international workshop on parallelism in inference systems held in Germany in December 1990. The topicof the workshop is still rather young and several papers in the book are overview articles intended to provide a first orientation toward some of the more intensively investigated subtopics. The main part of the book is a compilation of research papers on parallelization in special domains ofinference such as rewriting, automatic reasoning, logic programming, andconnectionist inference. Appended to the book is a collection of short project summaries received in response to a worldwide email call. The book is intended primarily for researchers working on inference systems who are interested in parallelizing their systems.
Parallel Processing for Artificial Intelligence 1
Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discusses parallel processing for semantic networks, which are widely used means for representing knowledge - methods which enable efficient and flexible processing of semantic networks are expected to have high utility for building large-scale knowledge-based systems. The third section explores the automatic parallel execution of production systems, which are used extensively in building rule-based expert systems - systems containing large numbers of rules are slow to execute and can significantly benefit from automatic parallel execution. The exploitation of parallelism for the mechanization of logic is dealt with in the fourth section. While sequential control aspects pose problems for the parallelization of production systems, logic has a purely declarative interpretation which does not demand a particular evaluation strategy. In this area, therefore, very large search spaces provide significant potential for parallelism. In particular, this is true for automated theorem proving. The fifth section considers the problem of constraint satisfaction, which is a useful abstraction of a number of important problems in AI and other fields of computer science. It also discusses the technique of consistent labeling as a preprocessing step in the constraint satisfaction problem. Section VI consists of two articles, each on a different, important topic. The first discusses parallel formulation for the Tree Adjoining Grammar (TAG), which is a powerful formalism for describing natural languages. The second examines the suitability of a parallel programming paradigm called Linda, for solving problems in artificial intelligence.Each of the areas discussed in the book holds many open problems, but it is believed that parallel processing will form a key ingredient in achieving at least partial solutions. It is hoped that the contributions, sourced from experts around the world, will inspire readers to take on these challenging areas of inquiry.
Parallel Symbolic Computing: Languages, Systems, and Applications
Author: Robert H. Halstead
language: en
Publisher: Springer Science & Business Media
Release Date: 1993-11-03
Parallel and distributed computing are becoming increasingly important as cost-effective ways to achieve high computational performance. Symbolic computations are notable for their use of irregular data structures and hence parallel symbolic computing has its own distinctive set of technical challenges. The papers in this book are based on presentations made at a workshop at MIT in October 1992. They present results in a wide range of areas including: speculative computation, scheduling techniques, program development tools and environments, programming languages and systems, models of concurrency and distribution, parallel computer architecture, and symbolic applications.