Constraint satisfaction problems are significant in the domain of automated reasoning for artificial intelligence. They can be applied to the modeling and solving of a wide range of combinatorial applications such as planning, scheduling and resource sharing in a variety of practical domains such as transportation, production, supply-chains, network management and human resourcemanagement. In this book we study new techniques for solving constraint satisfaction problems, with a special focus on solution adaptation applied to agent reasoning.

Study of new techniques for solving constraint satisfaction problems Special focus on solution adaptation applied to agent reasoning

Inhalt
Interchangeability and Solution Adaptation in Crisp CSPs.- Interchangeability in Soft CSPs.- Multi Agent Computation of Interchangeability in Distributed CSPs.- Interchangeability in Dynamic Environments.- Generic Case Adaptation Framework.- Conclusions.