@inproceedings{701bc05601a94872ba03e820baf81274,
title = "A Markov chain approach to analysis of cooperation in multi-agent search missions",
abstract = "We consider the effects of cueing in a cooperative search mission that involves several autonomous agents. Two scenarios are discussed: one in which the search is conducted by a number of identical search-and-engage vehicles, and one where these vehicles are assisted by a search-only (reconnaissance) asset. The cooperation between the autonomous agents is facilitated via cueing, i.e. the information transmitted to the agents by a searcher that has just detected a target. The effect of cueing on the target detection probability is derived from first principles using a Markov chain analysis. Exact solutions to Kolmogorov-type differential equations are presented, and existence of an upper bound on the benefit of cueing is demonstrated.",
author = "Jeffcoat, {David E.} and Krokhmal, {Pavlo A.} and Zhupanska, {Olesya I.}",
year = "2007",
doi = "10.1007/978-3-540-48271-0_11",
language = "English (US)",
isbn = "9783540482703",
series = "Lecture Notes in Economics and Mathematical Systems",
pages = "171--184",
editor = "Don Grundel and Panos Pardalos and Robert Murphey and Oleg Prokopyev",
booktitle = "Cooperative Systems",
}