@inproceedings{c180f020b07b451aa5378cccd3c5535c,
title = "Large pheromones: A case study with multi-agent physical A",
abstract = "Physical A*(PHA*) and its multi-agent version MAPHA*[3,4] are algorithm that find the shortest path between two points in an unknown real physical environment with one or many mobile agents. 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. Unlike small pheromones where 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.",
author = "Ariel Felner and Yaron Shoshani and Wagner, {Israel A.} and Bruckstein, {Alfred M.}",
year = "2004",
month = jan,
day = "1",
doi = "10.1007/978-3-540-28646-2_36",
language = "English",
isbn = "3540226729",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "366--373",
editor = "Marco Dorigo and Mauro Birattari and Christian Blum and Gambardella, {Luca M.} and Francesco Mondada and Thomas Stutzle",
booktitle = "Ant Colony Optimization and Swarm Intelligence - 4th International Workshop, ANTS 2004, Proceedings",
address = "Germany",
note = "4th International Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2004 ; Conference date: 05-09-2004 Through 08-09-2004",
}