We present a new algorithm for conformant probabilistic planning, which for a given horizon produces a plan that maximizes the probability of success under quantified uncertainty ...
Abstract. We give a lower bound for the error of any unitarily invariant algorithm learning half-spaces against the uniform or related distributions on the unit sphere. The bound i...
Abstract The current OWL 2 specification provides mechanisms for importing whole ontologies. This paper discusses the import of only a module of an external ontology, which is spe...
Abstract. We study a process calculus which combines both nondeterministic and probabilistic behavior in the style of Segala and Lynch’s probabilistic automata. We consider vario...
Domain independent planners can produce better-quality plans through the use of domain-speci c knowledge, typically encoded as search control rules. The planning-by-rewriting appro...