In this paper, we investigate the hypothesis that plan recognition can significantly improve the performance of a casebased reinforcement learner in an adversarial action selectio...
Current efficient planners employ an informed search guided by a heuristic function that is quite expensive to compute. Thus, ordering nodes in the search tree becomes a key issue,...
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, ...
Abstract. In order to facilitate the development of agent-based software, several agent programming languages and architectures, have been created. Plans in these architectures are...
Planning is vital to a wide range of domains, including robotics, military strategy, logistics, itinerary generation and more, that both humans and computers find difficult. Col...
Walter S. Lasecki, Jeffrey P. Bigham, James F. All...