A major challenge in constraint programming is to develop efficient generic approaches to solve instances of the constraint satisfaction problem (CSP). With this aim in mind, this book provides an accessible synthesis of the author''s research and work in this area, divided into four main topics: representation, inference, search, and learning. The results obtained and reproduced in this book have a wide applicability, regardless of the nature of the problem to be solved or the type of constraints involved, making it an extremely user-friendly resource for those involved in this field.

A major challenge in constraint programming is to develop efficient generic approaches to solve instances of the constraint satisfaction problem (CSP). With this aim in mind, this book provides an accessible synthesis of the author''s research and work in this area, divided into four main topics: representation, inference, search, and learning. The results obtained and reproduced in this book have a wide applicability, regardless of the nature of the problem to be solved or the type of constraints involved, making it an extremely user-friendly resource for those involved in this field.

A major challenge in constraint programming is to develop efficient generic approaches to solve instances of the constraint satisfaction problem (CSP). With this aim in mind, this book provides an accessible synthesis of the author''s research and work in this area, divided into four main topics: representation, inference, search, and learning. The results obtained and reproduced in this book have a wide applicability, regardless of the nature of the problem to be solved or the type of constraints involved, making it an extremely user-friendly resource for those involved in this field.