Introduction for Instructions Hetero Sensitivity of Pheromone with Ant Colony Optimization
Hisayuki Sasaoka
2014
Abstract
We have known that Ant Colony System (ACS) is one of powerful meta-heuristics and some researchers have reported the effectiveness of some applications using the algorithm. On the other hand, we have known that the algorithms have some problems when we employed it in multi-agent system and we have proposed a new method which is based on Max-Min Ant System (MM-AS), which is improved on ACS. This paper describes results of evaluation experiments with agents implemented our proposed method. In these experiments, we have prepared some different types of agents, which have hetero sensitivity of pheromone. The pheromones are deposited by agents and they help to search the shortest path for agents. The reason that we employ the agents are inspired by the report by researcher in the field of biology. Then we have prepared some conditions for RoboCup Rescue Simulation system (RCRS). To confirm the effectiveness, we have considered agents’ action in the simulation system.
DownloadPaper Citation
in Harvard Style
Sasaoka H. (2014). Introduction for Instructions Hetero Sensitivity of Pheromone with Ant Colony Optimization . In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-016-1, pages 305-310. DOI: 10.5220/0004921803050310
in Bibtex Style
@conference{icaart14,
author={Hisayuki Sasaoka},
title={Introduction for Instructions Hetero Sensitivity of Pheromone with Ant Colony Optimization},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2014},
pages={305-310},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004921803050310},
isbn={978-989-758-016-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Introduction for Instructions Hetero Sensitivity of Pheromone with Ant Colony Optimization
SN - 978-989-758-016-1
AU - Sasaoka H.
PY - 2014
SP - 305
EP - 310
DO - 10.5220/0004921803050310