Information-Driven Search Strategies in the Board Game of Clue 609
This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 39, NO. 3, JUNE 2009 607 Information-Driven Search Strategies in the Board Game of CLUE Silvia Ferrari, Senior Member, IEEE, and Chenghui Cai, Member, IEEE Abstract—This paper presents an information-driven sensor room in the mansion. Therefore, a game strategy must plan management problem, referred to as treasure hunt, which is rele- the suggestions’ sequence and enabling pawn motions based vant to mobile-sensor applications such as mine hunting, monitor- on the evidence that becomes available over time. By viewing ing, and surveillance. The objective is to infer a hidden variable or treasure by selecting a sequence of measurements associated the suggestions as measurements and the rooms as targets, an with multiple fixed targets distributed in the sensor workspace. approach is developed for computing optimal strategies from an The workspace is represented by a connectivity graph, where each influence diagram (ID) representation of the game. node represents a possible sensor deployment, and the arcs repre- As shown in [1] and [3], the treasure hunt is a basic sent possible sensor movements. An additive conditional entropy information-driven sensor management problem that is relevant reduction function is presented to efficiently compute the expected benefit of a measurement sequence over time. Then, the optimal to several mobile-sensor applications, such as robotic mine treasure hunt strategy is determined by a novel label-correcting hunting [4], cleaning [5], and monitoring of urban environments algorithm operating on the connectivity graph.
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