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Exploiting Adversarial Uncertainty in Robotic Patrolling: A Simulation-Based Analysis

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Advances in Computational Intelligence (IPMU 2012)

Abstract

Recently, several models for autonomous robotic patrolling have been proposed and analysed on a game-theoretic basis. The common drawback of such models are the assumptions required to apply game theory analysis. Such assumptions do not usually hold in practice, especially perfect knowledge of the adversary’s strategy, and the belief that we are facing always a best-responser. However, the agents in the patrolling scenario may take advantage of that fact. In this work, we try to analyse from an empirical perspective a patrolling model with an explicit topology, and take advantage of the adversarial uncertainty caused by the limited, imperfect knowledge an agent can acquire through simple observation. The first results we report are encouraging.

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© 2012 Springer-Verlag Berlin Heidelberg

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Villacorta, P.J., Pelta, D.A. (2012). Exploiting Adversarial Uncertainty in Robotic Patrolling: A Simulation-Based Analysis. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances in Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 300. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31724-8_55

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  • DOI: https://doi.org/10.1007/978-3-642-31724-8_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31723-1

  • Online ISBN: 978-3-642-31724-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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