Vrakas D., Vlahavas I.P. (eds.) Artificial Intelligence for Advanced Problem Solving Techniques

IGI Global, 2008, -389 p.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.Section I Automated Planning
Multi-Behicle Missions: Architecture and Algorithms for Distributed Online Planning
Extending Classical Planning for Time: Research Trends in Optimal and Suboptimal Temporal Planning
Section II Constraint Satisfaction and Scheduling
Principles of Constraint Processing
Stratified Constraint Satisfaction Networks in Synergetic Multi-Agent Simulations of Language Evolution
Soft-Constrained Linear Programming Support Vector Regression for Nonlinear Black-Box Systems Identification
Section III Machine Learning
Reinforcement Learning and Automated Planning: A Survey
Induction as a Search Procedure
Single- and Multi-Order Neurons for Recursive Unsupervised Learning
Section IV Optimization
Optimising Object Classification: Uncertain Reasoning-Based Analysis Using CaRBS Systematic Research Algorithms
Application of Fuzzy Optimization in Forecasting and Planning of Construction Industry
Rank Improvement Optimization Using PROMETHEE and Trigonometric Differential Evolution
Section V Genetic Algorithms and Programming
Parallelizing Genetic Algorithms: A Case Study
Using Genetic Programming to Extract Knowledge from Artificial Neural Networks