We describe the interface between a real-time resource allocation system with an AI planner in order to create fault-tolerant plans that are guaranteed to execute in hard real-tim...
Ella M. Atkins, Tarek F. Abdelzaher, Kang G. Shin,...
Reactive planning using assumptions is a well-known approach to tackle complex planning problems for nondeterministic, partially observable domains. However, assumptions may be wr...
Planners from the family of Graphplan (Graphplan, IPP, STAN...) are presently considered as the most efficient ones on numerous planning domains. Their partially ordered plans can...
Memory-bounded techniques have shown great promise in solving complex multi-agent planning problems modeled as DEC-POMDPs. Much of the performance gains can be attributed to pruni...
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, ...