TY - JOUR
T1 - Multi-agent physical A * with large pheromones
AU - Felner, Ariel
AU - Shoshani, Yaron
AU - Altshuler, Yaniv
AU - Bruckstein, Alfred M.
N1 - Funding Information:
This research was partly supported by Israeli Ministry of Science Infrastructure grant No. 3-942. We would like to thank the anonymous referees for their enlighting comments and suggestions which greatly contributed to the quality of this paper.
PY - 2006/1/1
Y1 - 2006/1/1
N2 - Physical A*(PHA*) and its multi-agent version MAPHA* are algorithms that find the shortest path between two points in an unknown real physical environment with one or many mobile agents [A. Felner et al. Journal of Artificial Intelligence Research, 21:631-679, 2004; A. Felner et al. Proceedings of the First International Joint Conference on Autonomous Agents and Multi-Agent Systems, Bologna, Italy, 2002:240-247]. Previous work assumed a complete sharing of knowledge between agents. Here we apply this algorithm to a more restricted model of communication which we call large pheromones, where agents communicate by writing and reading data at nodes of the graph that constitutes their environment. Previous works on pheromones usually assumed that only a limited amount of data can be written at each node. The large pheromones model assumes no limitation on the size of the pheromones and thus each agent can write its entire knowledge at a node. We show that with this model of communication the behavior of a multi-agent system is almost as good as with complete knowledge sharing. Under this model we also introduce a new type of agent, a communication agent, that is responsible for spreading the knowledge among other agents by moving around the graph and copying pheromones. Experimental results show that the contribution of communication agents is rather limited as data is already spread to other agents very well with large pheromones.
AB - Physical A*(PHA*) and its multi-agent version MAPHA* are algorithms that find the shortest path between two points in an unknown real physical environment with one or many mobile agents [A. Felner et al. Journal of Artificial Intelligence Research, 21:631-679, 2004; A. Felner et al. Proceedings of the First International Joint Conference on Autonomous Agents and Multi-Agent Systems, Bologna, Italy, 2002:240-247]. Previous work assumed a complete sharing of knowledge between agents. Here we apply this algorithm to a more restricted model of communication which we call large pheromones, where agents communicate by writing and reading data at nodes of the graph that constitutes their environment. Previous works on pheromones usually assumed that only a limited amount of data can be written at each node. The large pheromones model assumes no limitation on the size of the pheromones and thus each agent can write its entire knowledge at a node. We show that with this model of communication the behavior of a multi-agent system is almost as good as with complete knowledge sharing. Under this model we also introduce a new type of agent, a communication agent, that is responsible for spreading the knowledge among other agents by moving around the graph and copying pheromones. Experimental results show that the contribution of communication agents is rather limited as data is already spread to other agents very well with large pheromones.
KW - A
KW - Mobile agents
KW - Multi-agent communication models
KW - Pheromones
KW - Shortest path
UR - http://www.scopus.com/inward/record.url?scp=31344456694&partnerID=8YFLogxK
U2 - 10.1007/s10458-005-3943-y
DO - 10.1007/s10458-005-3943-y
M3 - Review article
AN - SCOPUS:31344456694
SN - 1387-2532
VL - 12
SP - 3
EP - 34
JO - Autonomous Agents and Multi-Agent Systems
JF - Autonomous Agents and Multi-Agent Systems
IS - 1
ER -