Publisher Summary The past few years have seen enormous progress in the performance of
Boolean satisfiability (SAT) solvers. Despite the worst-case exponential run time of all known …

The past five years have seen dramatic advances in planning algorithms, with an emphasis
on propositional methods such as GRAPHPLAN and compilers that convert planning …

Constraint programming is a powerful paradigm for solving combinatorial search problems
that draws on a wide range of techniques from artificial intelligence, computer science …

This book provides a comprehensive and much needed introduction to the field by one of its
foremost experts. It is beautifully written and presents a unifying framework capturing a wide …

Handbook of Knowledge Representation describes the essential foundations of Knowledge
Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up …

SATLIB is an online resource for SAT-related research established in June 1998. Its core
components, a benchmark suite of SAT instances and a collection of SAT solvers, aim to …

It is well known that the performance of a stochastic local search procedure depends upon
the setting of its noise parameter, and that the optimal setting varies with the problem …

Reactive Search integrates sub-symbolic machine learning techniques into search
heuristics for solving complex optimization problems. By automatically adjusting the working …

When multiple agents are in a shared environment, there usually exist con straints among
the possible actions of these agents. A distributed constraint satisfaction problem (distributed …

Planning research in Artificial Intelligence (AI) has often focused on problems where there
are cascading levels of action choice and complex interactions between actions. In contrast …