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Authors: Yan Meng and Ke Cao

Affiliation: Stevens Institute of Technology, United States

ISBN: 978-972-8865-66-5

Abstract: In a partially known dynamic environment, two multi-robot strategic searching approaches are proposed in this paper: utility greedy approach and game theoretic approach. It is assumed that a-priori probabilities of the targets’ distributions are provided. A one-step dynamic-programming is used to formalize the utility functions for both approaches, which not only depends on the targets’ distribution probabilities, but also on travel cost. Extensive simulation results shows that the proposed approaches are more efficient and robust compared to the other heuristic searching strategies, and game theoretic approach guaranteed better worst-case performance and be more robust to handle the environmental uncertainty.

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Paper citation in several formats:
Meng Y.; Cao K. and (2006). Strategic Searching Approaches in a Multi-Robot System.In Proceedings of the 2nd International Workshop on Multi-Agent Robotic Systems - Volume 1: MARS, (ICINCO 2006) ISBN 978-972-8865-66-5, pages 106-111. DOI: 10.5220/0001222501060111

@conference{mars06,
author={Yan Meng and Ke Cao},
title={Strategic Searching Approaches in a Multi-Robot System},
booktitle={Proceedings of the 2nd International Workshop on Multi-Agent Robotic Systems - Volume 1: MARS, (ICINCO 2006)},
year={2006},
pages={106-111},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001222501060111},
isbn={978-972-8865-66-5},
}

TY - CONF

JO - Proceedings of the 2nd International Workshop on Multi-Agent Robotic Systems - Volume 1: MARS, (ICINCO 2006)
TI - Strategic Searching Approaches in a Multi-Robot System
SN - 978-972-8865-66-5
AU - Meng, Y.
AU - Cao, K.
PY - 2006
SP - 106
EP - 111
DO - 10.5220/0001222501060111

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