Authors:
Shouhei Taga
1
;
Tomohumi Matsuzawa
2
;
Munehiro Takimoto
2
and
Yasushi Kambayashi
1
Affiliations:
1
Nippon Institute of Technology, Japan
;
2
Tokyo University of Science, Japan
Keyword(s):
Multi Agent, Mobile Agent, Ant Colony Optimization, Mobile Ad Hoc Network, Contingency Plan, Risk Management.
Related
Ontology
Subjects/Areas/Topics:
Agent Models and Architectures
;
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Autonomous Systems
;
Bioinformatics
;
Biomedical Engineering
;
Collective Intelligence
;
Cooperation and Coordination
;
Distributed and Mobile Software Systems
;
Distributed Problem Solving
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Mobile Agents
;
Multi-Agent Systems
;
Operational Research
;
Simulation
;
Software Engineering
;
Symbolic Systems
Abstract:
We propose a system that supports evacuation after a large-scale disaster. When a large-scale disaster
occurs, collecting information by using portable devices is difficult, because communication base stations
collapse and traffic congestion occurs. Evacuees are at a loss where they should go for safe places in lack of
information. In order to overcome these problems, we have proposed and evaluated a multi-agent system
that is built on MANET. Our aim is to let the users share information on MANET, and provide safe routes
to the destination by using collected information. In the previous paper, we proposed and implemented the
main functions of the proposed system, and performed feasibility study of the multi-agent system by using
simple simulator. In this paper, we report the revised system and investigate the relationships between the
number of the users and diffusivity of information, and the number of the generated mobile agents by using
newly constructed simulator. In the experime
nts for evaluation, we simulated a realistic situation by using
real map data and we took stochastic change of the situation into consideration, because the situation must
be getting worse by time elapses.
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