Classical computer science textbooks tell us that some problems are 'hard'. Yet many areas, from machine learning and computer vision to theorem proving and software verification, have defined their own set of tools for effectively solving complex problems. Tractability provides an overview of these different techniques, and of the fundamental concepts and properties used to tame intractability. This book will help you understand what to do when facing a hard computational problem. Can the problem be modelled by convex, or submodular functions? Will the instances arising in practice be of low...
Classical computer science textbooks tell us that some problems are 'hard'. Yet many areas, from machine learning and computer vision to theorem provi...
Decades of innovations in combinatorial problem solving have produced better and more complex algorithms. These new methods are better since they can solve larger problems and address new application domains. They are also more complex which means that they are hard to reproduce and often harder to fine-tune to the peculiarities of a given problem. This last point has created a paradox where efficient tools are out of reach of practitioners.
Autonomous search (AS) represents a new research field defined to precisely address the above challenge. Its major strength and originality...
Decades of innovations in combinatorial problem solving have produced better and more complex algorithms. These new methods are better since they c...
This book details key techniques in constraint networks, dealing in particular with constraint satisfaction, search, satisfiability, and applications in machine learning and constraint programming. Includes case studies.
This book details key techniques in constraint networks, dealing in particular with constraint satisfaction, search, satisfiability, and applications ...
