Open-loop plans in multi-robot POMDPs
msra
摘要
It is well known that it is much easier to find open-loop plans in partially-observable environments than it is to compute full policies. It is less well appreciated that open-loop plans can provide good (sometimes even optimal) performance in some real-world robotic planning problems. In this paper we identify several conditions under which open-loop plans provide good performance, and show that multi-agent tag (a recently-popular POMDP benchmark problem) satisfies these conditions. We take advantage of this result to compute plans for a team of three robots searching for an evader in an office environment.
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