Theoretical Study of Ant-based Algorithms for Multi-Agent Patrolling

This paper addresses the multi-agent patrolling problem, which consists for a set of autonomous agents to visit all the places of an unknown environment as regularly as possible. The proposed approach is based on the ant paradigm. Each agent can only mark and move according to its local perception of the environment. We study EVAW, a pheromone-based variant of the EVAP [3] and VAW [12]. The main novelty of the paper is the proof of some emergent spatial properties of the proposed algorithm. In particular we show that obtained cycles are necessarily of same length, which ensures an efficient spatial distribution of the agents. We also report some experimental results and discuss open questions concerning the proposed algorithm.

[1]  François Charpillet,et al.  Ant Colony Optimization applied to the Multi-Agent Patrolling Problem , 2006 .

[2]  Geber Ramalho,et al.  Combining Idleness and Distance to Design Heuristic Agents for the Patrolling Task , 2003 .

[3]  H. Van Dyke Parunak,et al.  Evolving adaptive pheromone path planning mechanisms , 2002, AAMAS '02.

[4]  Israel A. Wagner,et al.  ANTS: Agents on Networks, Trees, and Subgraphs , 2000, Future Gener. Comput. Syst..

[5]  H. Van Dyke Parunak,et al.  Performance of digital pheromones for swarming vehicle control , 2005, AAMAS '05.

[6]  Alexis Drogoul,et al.  Multi-agent Patrolling: An Empirical Analysis of Alternative Architectures , 2002, MABS.

[7]  Hoang-Nam Chu,et al.  Swarm Approaches for the Patrolling Problem, Information Propagation vs. Pheromone Evaporation , 2007 .

[8]  Jean-Louis Deneubourg,et al.  From local actions to global tasks: stigmergy and collective robotics , 2000 .

[9]  A. M. Bruckstein,et al.  Hamiltonian(t)-an ant-inspired heuristic for recognizing Hamiltonian graphs , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[10]  Marco Dorigo,et al.  Division of labor in a group of robots inspired by ants' foraging behavior , 2006, TAAS.

[11]  Marco Dorigo,et al.  Distributed Optimization by Ant Colonies , 1992 .

[12]  Jacques Ferber,et al.  From Tom Thumb to the Dockers: some experiments with foraging robots , 1993 .

[13]  Arnaud Glad,et al.  Swarm Approaches for the Patrolling Problem, Information Propagation vs. Pheromone Evaporation , 2007, 19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007).

[14]  Israel A. Wagner,et al.  Distributed covering by ant-robots using evaporating traces , 1999, IEEE Trans. Robotics Autom..