Multiagent Coordination by Stochastic Cellular Automata
Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence. Pages 1037-1041.
Abstract
A coordination mechanism for a system of sparsely communicating agents is described. The mechanism is based on a stochastic version of cellular automata. A parameter similar to a temperature can be tuned to change the behaviour of the system. It is found that the best coordination occurs near a phase transition between order and chaos. Coordination does not rely on any particular structure of the connections between agents, thus it may be applicable to a large array of sparsely communicating mobile robots.
Tim D. Barfoot, and Gabriele M. T. D'Eleuterio. 2001. Multiagent Coordination by Stochastic Cellular Automata. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, IJCAI-01. IJCAI, 1037–1041. https://ijcai.org/proceedings/2001/140
Barfoot, T. D., & D'Eleuterio, G. M. T. (2001). Multiagent Coordination by Stochastic Cellular Automata. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, IJCAI-01 (pp. 1037–1041). IJCAI. https://ijcai.org/proceedings/2001/140
@inproceedings{ijcai2001p140,
title = {Multiagent Coordination by Stochastic Cellular Automata},
author = {Barfoot, Tim D. and D'Eleuterio, Gabriele M. T.},
booktitle = {Proceedings of the Seventeenth International Joint Conference on
Artificial Intelligence, {IJCAI-01}},
publisher = {International Joint Conferences on Artificial Intelligence},
pages = {1037--1041},
year = {2001},
url = {https://ijcai.org/proceedings/2001/140},
}
TY - CPAPER TI - Multiagent Coordination by Stochastic Cellular Automata AU - Barfoot, Tim D. AU - D'Eleuterio, Gabriele M. T. T2 - Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, IJCAI-01 PB - International Joint Conferences on Artificial Intelligence PY - 2001 SP - 1037 EP - 1041 UR - https://ijcai.org/proceedings/2001/140 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: