The max-sum labeling problem, defined as maximizing a sum of binary (ie, pairwise)
functions of discrete variables, is a general NP-hard optimization problem with many …

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

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

Analogy—recalling familiar past situations to deal with novel ones—is a mental tool that
everyone uses. Analogy can provide invaluable creative insights, but it can also lead to …

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 …

Metaheuristics are the most exciting development in approximate optimization techniques of
the last two decades. They have had widespread successes in attacking a variety of difficult …

We report results from large-scale experiments in satisability testing. As has been observed
by others, testing the satis ability of random formulas often appears surprisingly easy. Here …

Unpredictability in the running time of complete search procedures can often be explained
by the phenomenon of “heavy-tailed cost distributions”, meaning that at any time during the …

Writing the second edition of this text was a wonderful opportunity for a more mature
presentation than I was able to give 13 years ago. The intent still is to give a self-contained …

We develop a formalism called a distributed constraint satisfaction problem (distributed
CSP) and algorithms for solving distributed CSPs. A distributed CSP is a constraint …