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A Theoretical Analysis of Multi-Agent Patrolling Strategies Patrolling = moving through a territory « visiting » areas The patrolling problem = given a.

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Presentation on theme: "A Theoretical Analysis of Multi-Agent Patrolling Strategies Patrolling = moving through a territory « visiting » areas The patrolling problem = given a."— Presentation transcript:

1 A Theoretical Analysis of Multi-Agent Patrolling Strategies Patrolling = moving through a territory « visiting » areas The patrolling problem = given a graph representing a territory, how to move n agents around the graph, such that nodes are visited as often as possible Applications Multi-robot patrolling, computer games, military applications Approaches –Reactive agent based architecture (agents move towards least visited nodes) –Partition based approach (1 agent per region) –Combinatorial optimization approach

2 Cyclic strategies 1) Compute a cycle covering the entire graph: 2) Let agents turn around this cycle, 1 2 3 4 56 7 8

3 Partition-based strategies 1) Compute a partition of the graph in n regions: 2) Let each agent patrol in a region, 1 2 3 4 56 etc…

4 Results Cyclic strategies single agent case: if the cycle is obtained is the optimal TSP cycle (traveling salesman problem), then strategy is optimal Multi-agent case: If cycle is obtained with a TSP approximation algorithm, then Max visiting time < 3xoptimal + c (near optimal!) Partition-based strategies Max visiting time > optimal(cyclic) - c Thus, cyclic-based is probably nearly always better !! Conclusion: Cyclic-based approach is excellent except when c (length of longest edge) is big, in which case partitioning is a good idea! Experimentally : cyclic strategy is at least as good as other state-of-the-art strategies


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