loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Author: Hisayuki Sasaoka

Affiliation: Asahikawa National College of Technology, Japan

Keyword(s): Multi-agent System, Swarm Intelligence, Pheromone Communication, Ant Colony Optimization.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Bioinformatics ; Biomedical Engineering ; Computational Intelligence ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Evolutionary Computing ; Informatics in Control, Automation and Robotics ; Information Systems Analysis and Specification ; Intelligent Control Systems and Optimization ; Knowledge Discovery and Information Retrieval ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Machine Learning ; Methodologies and Technologies ; Multi-Agent Systems ; Operational Research ; Simulation ; Soft Computing ; Software Engineering ; Symbolic Systems

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.94.102.228

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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; ISSN 2184-433X, SciTePress, pages 305-310. DOI: 10.5220/0004921803050310

@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},
issn={2184-433X},
}

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
IS - 2184-433X
AU - Sasaoka, H.
PY - 2014
SP - 305
EP - 310
DO - 10.5220/0004921803050310
PB - SciTePress