Operations Research and Artificial Intelligence: The Integration of Problem-Solving StrategiesDonald E. Brown, Chelsea C. White III Springer Science & Business Media, 2012. gada 6. dec. - 512 lappuses 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. |
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Genetic Algorithms Applications to Set Covering | 29 |
Discovering and Refining Algorithms Through | 59 |
Using Probabilities as Control Knowledge | 81 |
On the Marshalling of Evidence and the Structuring | 105 |
Hybrid Systems for Failure Diagnosis | 141 |
Default Reasoning Through Integer Linear | 171 |
The Problem of Determining Membership Values | 197 |
Applications of Utility Theory in Artificial | 217 |
A Computer Model | 249 |
Eliciting Knowledge Representation Schema | 277 |
A Knowledge Base for Integer ProgrammingA | 317 |
Performance Analysis and Complexity Management | 370 |
Measuring and Managing Complexity | 387 |
Pragmatic InformationSeeking Strategies | 427 |
An Integrated Management Information System | 481 |
About the Authors | 497 |
Citi izdevumi - Skatīt visu
Operations Research and Artificial Intelligence: The Integration of Problem ... Donald E. Brown,Chelsea C. White III Ierobežota priekšskatīšana - 1990 |
Operations Research and Artificial Intelligence: The Integration of Problem ... Donald E. Brown,Chelsea C. White III Priekšskatījums nav pieejams - 2011 |
Operations Research and Artificial Intelligence: The Integration of Problem ... Donald E. Brown,Chelsea C. White III Priekšskatījums nav pieejams - 2011 |
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alternative process plan analysis applications approach argument Artificial Intelligence attribute values automated causal clauses complexity compromise Computer Science conclusion conjunctive normal form constraints cost crossover decision maker determine domain Engineering evaluation functions event evidence evidential example expert system failure fuzzy set genetic algorithm goal graph greedy Grefenstette heuristic hypotheses incidence matrix inference inference engine inferential influence diagrams inspection integer programming involves knowledge base knowledge representation knowledge-based large number logical LP formulation machine learning Management Science mathematical programming matrix membership values Meta-rules methods minimize nodes objective function observed variables Operations Research optimization paper path payoff performance possible potential probabilistic probability problem type problem-solver production represent representation rule-based S₁ scheduling problems selection set covering problems situation solution solving strategy structure Sycara techniques traveling salesman problems uncertainty University updating utility function utility theory Validator variable of interest