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

With all the material available in the field of artificial intelligence (AI) and soft computing-
texts, monographs, and journal articles-there remains a serious gap in the literature. Until …

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 …

Stochastic algorithms are among the best methods for solving computationally hard search
and reasoning problems. The run time of such procedures can vary significantly from …

We study the runtime distributions of backtrack procedures for propositional satisfiability and
constraint satisfaction. Such procedures often exhibit a large variability in performance. Our …

This paper provides a computational characterization of coherence that applies to a wide
range of philosophical problems and psychological phenomena. Maximizing coherence is a …

Constraint programming offers facilities for problem modelling, constraint propagation and
search. This paper discusses the resulting benefits for practical applications which exploit …

When reasoning about deontic rules (what one may, should, or should not do in a given set
of circumstances), reasoners adopt a violation‐detection strategy, a strategy they do not …

Combinatorial search methods often exhibit a large variability in performance. We study the
cost profiles of combinatorial search procedures. Our study reveals some intriguing …

Planning is a central activity in many areas including robotics, manufacturing, space mission
sequencing, and logistics. As the size and complexity of planning problems grow, there is …