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We designed and constructed a system that includes aircraft, ground vehicles, and throwable sensors to search a semi-forested region that was partially covered by foliage. The system contained 4 radio-controlled (RC) trucks, 2 aircraft, and 30 SensorMotes (throwable sensors). We also investigated communications links, search strategies, and system architecture. Our system is designed to be low-cost,...
We propose a new approximate algorithm, LA- JIV (lookahead J-MDP information value), to solve oracular partially observable Markov decision problems (OPOMDPs), a special type of POMDP that rather than standard observations includes an "oracle" that can be consulted for full state information at a fixed cost. We previously introduced JIV (J-MDP information value) to solve OPOMDPs, an heuristic...
We introduce the oracular partially observable Markov decision process (OPOMDP), a type of POMDP in which the world produces no observations; instead there is an "oracle," available in any state, that tells the agent its exact state for a fixed cost. The oracle may be a human or a highly accurate sensor. At each timestep the agent must choose whether to take a domain-level action or consult...
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