Distributed Anonymous Mobile Robots: Formation of Geometric Patterns
SIAM Journal on Computing
Efficiently searching a graph by a smell-oriented vertex process
Annals of Mathematics and Artificial Intelligence
A Theoretical Analysis of Multi-Agent Patrolling Strategies
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Probabilistic Multiagent Patrolling
SBIA '08 Proceedings of the 19th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
Multi-a(ge)nt Graph Patrolling and Partitioning
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Developing a Deterministic Patrolling Strategy for Security Agents
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Multi-agent patrolling: an empirical analysis of alternative architectures
MABS'02 Proceedings of the 3rd international conference on Multi-agent-based simulation II
Multi-agent deployment on a ring graph
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Negotiator agents for the patrolling task
IBERAMIA-SBIA'06 Proceedings of the 2nd international joint conference, and Proceedings of the 10th Ibero-American Conference on AI 18th Brazilian conference on Advances in Artificial Intelligence
Boundary patrolling by mobile agents with distinct maximal speeds
ESA'11 Proceedings of the 19th European conference on Algorithms
Stigmergic coverage algorithm for multi-robot systems (demonstration)
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
A multi-robot coverage approach based on stigmergic communication
MATES'12 Proceedings of the 10th German conference on Multiagent System Technologies
Optimal patrolling of fragmented boundaries
Proceedings of the twenty-fifth annual ACM symposium on Parallelism in algorithms and architectures
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We introduce a novel multi-agent patrolling strategy. By assumption, the swarm of agents performing the task consists of very low capability ant-like agents. The agents have little memory, they can not communicate and their sensing abilities are local. Furthermore, the agents do not possess any knowledge regarding the graph or the swarm size. However, the agents may mark the graph vertices with pheromone stamps which can later be sensed. These markings are used as a primitive form of distributed memory and communication. The proposed strategy is a bundle of two algorithms. A single agent (the "leader") is responsible of finding a short cycle which covers the graph, and this is achieved using a "cycle finding" algorithm. All other agents follow that cycle while maintaining even gaps between them using a "spreading algorithm". We prove that the algorithms converge within a finite expected time. After convergence, the maximum time lag between two successive visits to any vertex using the proposed strategy is at most 4 k/k-1 lmax/lmin times the optimal, where the optimal time is bounded from below by nċlmin/k, and where lmax (lmin) is the longest (shortest) edge in the graph and k is the swarm size. The "cycle finding" algorithm is robust i.e. in case the graph changes, the leader autonomously finds a new patrolling route. The "spreading algorithm" is scalable and robust. In case the patrolling cycle or the number of agents change during run (e.g. as a result of an agent break down) the agents autonomously redeploy uniformly over the patrolling cycle.