Abstract. In this work a model for planning with multivalued fluents and graded actions, based on the infinite valued Lukasiewicz logic, is introduced. In multivalued planning, flu...
Marco Baioletti, Alfredo Milani, Valentina Poggion...
Markov Decision Processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given...
Heuristic search is a leading approach to domain-independent planning. For cost-optimal planning, however, existing admissible heuristics are generally too weak to effectively gui...
Patrik Haslum, Adi Botea, Malte Helmert, Blai Bone...
Dynamic programming algorithms have been successfully applied to propositional stochastic planning problems by using compact representations, in particular algebraic decision diag...
In our research we study rational agents which learn how to choose the best conditional, partial plan in any situation. The agent uses an incomplete symbolic inference engine, emp...