Peter Stone's Selected Publications

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When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing

Fei Fang, Peter Stone, and Milind Tambe. When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2015.
Winner of Computational Sustainability Track Outstanding Paper Awardat IJCAI 2015

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Abstract

Building on the successful applications of Stackelberg Security Games (SSGs) to protect infrastructure, researchers have begun focusing on applying game theory to green security domains such as protection of endangered animals and fish stocks. Previous efforts in these domains optimize defender strategies based on the standard Stackelberg assumption that the adversaries become fully aware of the defender's strategy before taking action. Unfortunately, this assumption is inappropriate since adversaries in green security domains often lack the resources to fully track the defender strategy. This paper (i) introduces Green Security Games (GSGs), a novel game model for green security domains with a generalized Stackelberg assumption; (ii) provides algorithms to plan effective sequential defender strategies --- such planning was absent in previous work; (iii) proposes a novel approach to learn adversary models that further improves defender performance; and (iv) provides detailed experimental analysis of proposed approaches.

BibTeX Entry

@InProceedings{IJCAI15-fei,
  title={When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing},
  author={Fei Fang and Peter Stone and Milind Tambe},
  booktitle={Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI)},
  year={2015},
  month={July},
  abstract={
            Building on the successful applications of Stackelberg
            Security Games (SSGs) to protect infrastructure,
            researchers have begun focusing on applying game theory to
            green security domains such as protection of endangered
            animals and fish stocks. Previous efforts in these domains
            optimize defender strategies based on the standard
            Stackelberg assumption that the adversaries become fully
            aware of the defender's strategy before taking
            action. Unfortunately, this assumption is inappropriate
            since adversaries in green security domains often lack the
            resources to fully track the defender strategy. This paper
            (i) introduces Green Security Games (GSGs), a novel game
            model for green security domains with a generalized
            Stackelberg assumption; (ii) provides algorithms to plan
            effective sequential defender strategies --- such planning
            was absent in previous work; (iii) proposes a novel
            approach to learn adversary models that further improves
            defender performance; and (iv) provides detailed
            experimental analysis of proposed approaches.
  },
  wwwnote={Winner of <b>Computational Sustainability Track Outstanding Paper Award</b>at <a href="http://ijcai-15.org/">IJCAI 2015</a>},
}

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