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Artificial Intelligence for Advanced Problem Solving Techniques

By: Ioannis Vlahavas (Editor), Dimitris Vrakas (Editor)

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Hardcover | 1 February 2008

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Hardcover
390 Pages

Dimensions(cm)
27.94 x 21.59 x 2.24

Hardcover

$445.75

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One of the most important functions of artificial intelligence, automated problem solving, consists mainly of the development of software systems designed to find solutions to problems. These systems utilize a search space and algorithms in order to reach a solution. Artificial Intelligence for Advanced Problem Solving Techniques offers scholars and practitioners cutting-edge research on algorithms and techniques such as search, domain independent heuristics, scheduling, constraint satisfaction, optimization, configuration, and planning, and highlights the relationship between the search categories and the various ways a specific application can be modeled and solved using advanced problem solving techniques.

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You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Expert Systems & Knowledge-Based Systems Education Open Learning Economics, Finance, Business and Management Business Applications

Automated Planning
Multi-Vehicle Missions: Architecture and Algorithms for Distributed Online Planning	p. 1
Extending Classical Planning for Time: Research Trends in Optimal and Suboptimal Temporal Planning	p. 23
Constraint Satisfaction and Scheduling
Principles of Constraint Processing	p. 63
Stratified Constraint Satisfaction Networks in Synergetic Multi-Agent Simulations of Language Evolution	p. 107
Soft-Constrained Linear Programming Support Vector Regression for Nonlinear Black-Box Systems Identification	p. 137
Machine Learning
Reinforcement Learning and Automated Planning: A Survey	p. 148
Induction as a Search Procedure	p. 166
Single- and Multi-Order Neurons for Recursive Unsupervised Learning	p. 217
Optimization
Optimising Object Classification: Uncertain Reasoning-Based Analysis Using CaRBS Systematic Search Algorithms	p. 234
Application of Fuzzy Optimization in Forecasting and Planning of Construction Industry	p. 254
Rank Improvement Optimization Using PROMETHEE and Trigonometric Differential Evolution	p. 266
Genetic Algorithms and Programming
Parallelizing Genetic Algorithms: A Case Study	p. 284
Using Genetic Programming to Extract Knowledge from Artificial Neural Networks	p. 308
Compilation of References	p. 328
About the Contributors	p. 359
Index	p. 366
Table of Contents provided by Blackwell. All Rights Reserved.

Artificial Intelligence for Advanced Problem Solving Techniques

At a Glance

Hardcover

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