This paper investigates the impact of symbolic search for solving domain-independent action planning problems with binary decision diagrams (BDDs). Polynomial upper and exponential...
The problem of learning the structure of Bayesian networks from complete discrete data with a limit on parent set size is considered. Learning is cast explicitly as an optimisatio...
— Hyper-heuristics or “heuristics to chose heuristics” are an emergent search methodology that seeks to automate the process of selecting or combining simpler heuristics in o...
Abstract. This paper presents a simple iterated local search metaheuristic incorporating a k-opt local search (KLS), called Iterated KLS (IKLS for short), for solving the maximum c...
Combinatorial covering arrays have been used in several testing approaches. This paper first discusses some existing methods for finding such arrays. Then a SAT-based approach a...