In this paper, we describe the partially observable Markov decision process pomdp approach to nding optimal or near-optimal control strategies for partially observable stochastic ...
Anthony R. Cassandra, Leslie Pack Kaelbling, Micha...
We dene the probabilistic planning problem in terms of a probability distribution over initial world states, a boolean combination of goal propositions, a probability threshold, ...
An ongoing debate in text understanding efforts centers on the use of pattern-matching techniques, which some have characterized as "designed to ignore as much text as possib...
We propose a representation of concurrent actions; rather than invent a new formalism, we model them within the standard situation calculus by introducing the notions of global ac...
In this paper a planning framework based on Ant Colony Optimization techniques is presented. It is well known that finding optimal solutions to planning problems is a very hard co...
Marco Baioletti, Alfredo Milani, Valentina Poggion...