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Rollout Algorithms for Wireless Sensor Network-Assisted Target Search

We consider a mobile, autonomous searcher that aims to find the source of a broadcast message in a network of location-agnostic wireless sensor nodes. In certain types of networks, the hop count of the broadcast message, given the distance from the source node, is well approximated by a simple parametric distribution. The mobile searcher can interrogate a nearby node to obtain, with a given success probability, the hop count of the broadcast message. The search is modeled as an infinite horizon, undiscounted cost, and partially observable Markov decision process. A computationally efficient approximate online solution is obtained through policy rollout using a novel heuristic. Simulation results show that our rollout approach outperforms commonly used search methods based on a mutual information utility. We quantify the loss due to the use of an approximate hop count observation model and study the effect of statistical dependence between observations. Furthermore, we discuss how to account for this dependence by adapting an integer autoregressive model for the hop count.