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Decentralized Bayesian Search Using Approximate Dynamic Programming Methods

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3 Author(s)
Yijia Zhao ; Dept. of Syst. & Inf. Eng., Univ. of Virginia, Charlottesville, VA ; Patek, S.D. ; Beling, P.A.

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 times 5 grid.

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Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on  (Volume:38 ,  Issue: 4 )