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Decentralized Bayesian search using approximate dynamic programming methods
Yijia Zhao1, Stephen D Patek, Peter A Beling
1Department of Systems and Information Engineering, University of Virginia, Charlottesville, VA 22904 USA. yz4k@virginia.edu
Abstract:
We consider decentralized Bayesian search problems that involve a team of multiple autonomous agents searching for targets on a network of search points operating under the following constraints: 1) interagent communication is limited; 2) the agents do not have the opportunity to agree in advance on how to resolve equivalent but incompatible strategies; and 3) each agent lacks the ability to control or predict with certainty the actions of the other agents. We formulate the multiagent search-path-planning problem as a decentralized optimal control problem and introduce approximate dynamic heuristics that can be implemented in a decentralized fashion. After establishing some analytical properties of the heuristics, we present computational results for a search problem involving two agents on a 5 x 5 grid.
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