Despite a big progress in solving planning problems, more complex problems still remain hard and challenging for existing planners. One of the most promising research directions i...
Compared to optimal planners, satisficing planners can solve much harder problems but may produce overly costly and long plans. Plan quality for satisficing planners has become in...
Abstract. We describe a way to improve the performance of MDP planners by modifying them to use lower and upper bounds to eliminate non-optimal actions during their search. First, ...
We study computational problems that arise in the context of iterated dominance in anonymous games, and show that deciding whether a game can be solved by means of iterated weak d...
In this paper, we present a new algorithm that integrates recent advances in solving continuous bandit problems with sample-based rollout methods for planning in Markov Decision P...
Christopher R. Mansley, Ari Weinstein, Michael L. ...