Operations research and artificial intelligence : the integration of problem-solving strategies
著者
書誌事項
Operations research and artificial intelligence : the integration of problem-solving strategies
Kluwer Academic Publishers, c1990
大学図書館所蔵 全37件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
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.
「Nielsen BookData」 より