An Empirical Method for Benchmarking Multi-Robot Patrol Strategies in Adversarial Environments

Author:

Ward James C.1ORCID,Hunt Edmund R.1ORCID

Affiliation:

1. University of Bristol, Bristol, United Kingdom

Funder

Engineering and Physical Sciences Research Council

Publisher

ACM

Reference18 articles.

1. Multi-Robot Adversarial Patrolling: Facing a Full-Knowledge Opponent;Agmon N.;Journal of Artificial Intelligence Research,2011

2. N. Agmon and S. Kraus. 2019. Multi-Robot Adversarial Patrolling: Handling Sequential Attack. Artifical Intelligence 274 (February 2019) 1--25. N. Agmon and S. Kraus. 2019. Multi-Robot Adversarial Patrolling: Handling Sequential Attack. Artifical Intelligence 274 (February 2019) 1--25.

3. Decentralized and Nondeterministic Multi-Robot Area Patrolling in Adversarial Environments

4. A. B. Asghar and Smith S. L . 2019. Stochastic Patrolling in Adversarial Settings . In Proceedings of the 2016 American Control Conference (ACC) . Boston, USA, 6435--6440. A. B. Asghar and Smith S. L. 2019. Stochastic Patrolling in Adversarial Settings. In Proceedings of the 2016 American Control Conference (ACC). Boston, USA, 6435--6440.

5. A. B. Asghar and S. L. Smith . 2018. A Patrolling Game for Adversaries with Limited Observation Time . In Proceedings of the 2018 IEEE Conference on Decision and Control (CDC) . Miami Beach, USA, 3305--3310. A. B. Asghar and S. L. Smith. 2018. A Patrolling Game for Adversaries with Limited Observation Time. In Proceedings of the 2018 IEEE Conference on Decision and Control (CDC). Miami Beach, USA, 3305--3310.

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Attrition-Aware Adaptation for Multi-Agent Patrolling;IEEE Robotics and Automation Letters;2024-08

2. Shaping Multi-Robot Patrol Performance with Heterogeneity in Individual Learning Behavior;2024 IEEE International Conference on Development and Learning (ICDL);2024-05-20

3. Collective Anomaly Perception During Multi-Robot Patrol: Constrained Interactions Can Promote Accurate Consensus;Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing;2024-04-08

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