Extending Algorithms for Mobile Robot Patrolling in the Presence of Adversaries to More Realistic Settings

Patrolling environments by means of autonomous mobile robots has received an increasing attention in the last few years. The interest of the agent community is mainly in the development of effective patrolling strategies. Approaches based on game theory have been demonstrated to be very effective. They model the patrolling situation as a two-player leader-follower game, where the patroller is the leader and the intruder is the follower. These models present several limitations that prevent their use in realistic settings. In this paper, we extend the most general model from the state of the art along two directions, we propose algorithms to solve efficiently our extensions, and we experimentally evaluate them.

[1]  Nicola Basilico,et al.  Finding the optimal strategies for robotic patrolling with adversaries in topologically-represented environments , 2009, 2009 IEEE International Conference on Robotics and Automation.

[2]  Vincent Conitzer,et al.  Complexity of (iterated) dominance , 2005, EC '05.

[3]  Sarit Kraus,et al.  Deployed ARMOR protection: the application of a game theoretic model for security at the Los Angeles International Airport , 2008, AAMAS.

[4]  M. Dufwenberg Game theory. , 2011, Wiley interdisciplinary reviews. Cognitive science.

[5]  Brian W. Kernighan,et al.  AMPL: A Modeling Language for Mathematical Programming , 1993 .

[6]  Sarit Kraus,et al.  Playing games for security: an efficient exact algorithm for solving Bayesian Stackelberg games , 2008, AAMAS.

[7]  B. Stengel,et al.  Leadership with commitment to mixed strategies , 2004 .

[8]  Anthony Stentz,et al.  Optimal and efficient path planning for partially-known environments , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[9]  Francesco Amigoni,et al.  A Game-Theoretic Approach to Determining Efficient Patrolling Strategies for Mobile Robots , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[10]  Sushil J. Louis,et al.  Using a Genetic Algorithm to Explore A*-like Pathfinding Algorithms , 2007, 2007 IEEE Symposium on Computational Intelligence and Games.

[11]  Sarit Kraus,et al.  Multi-robot perimeter patrol in adversarial settings , 2008, 2008 IEEE International Conference on Robotics and Automation.

[12]  Nicola Gatti,et al.  Game Theoretical Insights in Strategic Patrolling: Model and Algorithm in Normal-Form , 2008, ECAI.

[13]  Nicola Basilico,et al.  Leader-follower strategies for robotic patrolling in environments with arbitrary topologies , 2009, AAMAS.

[14]  Elbert E. N. Macau,et al.  Patrol Mobile Robots and Chaotic Trajectories , 2007 .

[15]  Nicola Basilico,et al.  Developing a Deterministic Patrolling Strategy for Security Agents , 2009, 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology.

[16]  Sarit Kraus,et al.  Deployed ARMOR protection: the application of a game theoretic model for security at the Los Angeles International Airport , 2008, AAMAS 2008.

[17]  Sarit Kraus,et al.  An efficient heuristic approach for security against multiple adversaries , 2007, AAMAS '07.

[18]  Sui Ruan,et al.  Patrolling in a Stochastic Environment , 2005 .