[1] KOOPMAN B O.The theory of searchpart I:kinematic bases［J］.Operations Research19564(3):324-346.

[2] KOOPMAN B O.The theory of searchpart II:target detection［J］.Operations Research19564(5):503-531.

[3] KOOPMAN B O.The theory of searchpart III:the optimum distribution of searching effort［J］.Operations Research 19575(5):613-626.

[4] STONE L D.Theory of optimal search［M］.New York: Elsevier1976.

[10] ALHAKEEM SVARSHNEY P K.Decentralized Bayesian detection with feedback［J］.IEEE Transactions on SystemsManand Cybernetics-Part A:Systems and Humans199626(4):503-513.

[12] YANG Y LMINAI APOLYCARPOU M.Decentralized cooperative search in UAVs using opportunistic learning［C］//AIAA GuidanceNavigationand Control Conference and Exhibit2002:1-10.

[14] NAJEMNIK J,GEISLER W S.Optimal eye movement stra-tegies in visual search［J］.Nature2005434:387-391.

[19] WONG E MBOURGAULT FFURUKAWA T.Multi-vehicle Bayesian search for multiple lost targets［C］//Proceedings of the IEEE International Conference on Robotics and Automation, IEEE2005:3169-3174.

[20] CHUNG T HBURDICK J W.A decision-making framework for control strategies in probabilistic search［C］//Proceedings of IEEE International Conference on Robotics and AutomationIEEE2007:4386-4393.

[21] CHUNG T HBURDICK J W.Multi-agent probabilistic search in a sequential decision-theoretic framework［C］//IEEE International Conference on Robotics and Automation IEEE2008:146-151.

[22] CHUNG T HBURDICK J W.Analysis of search decision making using probabilistic search strategies［J］.IEEE Transactions on Robotics201228(1):132-144.

[23] THRUN SBURGARD WFOX D.Probabilistic robotics［M］.Los Angeles:MIT Press2005.

[24] WANG TYANG J.A heuristic method for learning Bayesian networks using discrete particle swarm optimization［J］.Knowledge and Information Systems201024(2):269-281.