A search game for optimizing information collection in UUV mission planning

This paper addresses search planning to find hidden objects in undersea environments where the sensor detection process is subject to false alarms with a geographically varying likelihood. We develop a game-theoretic approach for maximizing the information flow that occurs as a multi-agent collaborative search is conducted over a bounded region. To accomplish this, we apply 1) a search channel formalism to the discrete search paradigm to formulate information measures as a function of searcher regional visitation and 2) a Receiver Operator Characteristic (ROC) analysis to map search strategies to ROC operating points which, in turn, define the properties of the search channel. This enables us to formulate a search game where the cost is driven by expended search effort and the payout is in terms of the information collected. We describe a new algorithmic capability for solving the search allocation problem of multiple unmanned undersea vehicles that can collaborate in their efforts to resolve false alarm outcomes. We discuss the properties of the information measure developed for a repeated look over the search channel and examine the impact of setting ROC operating points to their game equilibrium values. Doing so enables the regional visitation to be determined via a greedy scheduling solution. Results are presented to show the dominance of this approach over alternative ROC strategies and to demonstrate the capability to take advantage of known non-homogeneity in the search environment.