Operations Research and Artificial Intelligence: The Integration of Problem-Solving Strategies / Edition 1

by Donald E. Brown, Chelsea C. White III

Overview

The purpose of this book is to introduce and explain research at the boundary between two fields that view problem solving from different perspectives. Researchers in operations research and artificial intelligence have traditionally remained separate in their activities. Recently, there has been an explosion of work at the border of the two fields, as members of both communities seek to leverage their activities and resolve problems that remain intractable to pure operations research or artificial intelligence techniques. This book presents representative results from this current flurry of activity and provides insights into promising directions for continued exploration. This book should be of special interest to researchers in artificial intelligence and operations research because it exposes a number of applications and techniques, which have benefited from the integration of problem solving strategies. Even researchers working on different applications or with different techniques can benefit from the descriptions contained here, because they provide insight into effective methods for combining approaches from the two fields. Additionally, researchers in both communities will find a wealth of pointers to challenging new problems and potential opportunities that exist at the interface between operations research and artificial intelligence. In addition to the obvious interest the book should have for members of the operations research and artificial intelligence communities, the papers here are also relevant to members of other research communities and development activities that can benefit from improvements to fundamental problem solving approaches.

Product Details

ISBN-13:	9780792391067
Publisher:	Springer Netherlands
Publication date:	08/31/1990
Edition description:	1990
Pages:	512
Product dimensions:	8.27(w) x 11.69(h) x 0.24(d)

Table of Contents

I. Search.- Toward the Modeling, Evaluation and Optimization of Search Algorithms.- Genetic Algorithms Applications to Set Covering and Traveling Salesman Problems.- Discovering and Refining Algorithms Through Machine Learning.- II. Uncertainty Management.- Using Probabilities as Control Knowledge to Search for Relevant Problem Models in Automated Reasoning.- On the Marshalling of Evidence and the Structuring of Argument.- Hybrid Systems for Failure Diagnosis.- III. Imprecise Reasoning.- Default Reasoning Through Integer Linear Programming.- The Problem of Determining Membership Values in Fuzzy Sets in Real World Situations.- IV. Decision Analysis and Decision Support.- Applications of Utility Theory in Artificial Intelligence Research.- A Multicriteria Stratification Framework for Uncertainty and Risk Analysis.- Dispute Mediation: A Computer Model.- V. Mathematical Programming and AI.- Eliciting Knowledge Representation Schema for Linear Programming Formulation.- A Knowledge Base for Integer Programming—A Meta-OR Approach.- VI. Performance Analysis and Complexity Management of Expert Systems.- Validator, A Tool for Verifying and Validating Personal Computer Based Expert Systems.- Measuring and Managing Complexity in Knowledge-Based Systems: A Network and Mathematical Programming Approach.- Pragmatic Information-Seeking Strategies for Expert Classification Systems.- VII. Applications.- A Knowledge- and Optimization-Based Approach to Scheduling in Automated Manufacturing Systems.- An Integrated Management Information System for Wastewater Treatment Plants.- About the Authors.