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.