scholarly journals Time Critical Mass Evacuation Simulation Combining A Multi- Agent System and High-Performance Computing

2017 ◽  
Author(s):  
Leonel Aguilar ◽  
Maddegedara Lalith ◽  
Muneo Hori
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Critical Mass ◽  
Multi Agent System ◽  
Agent System ◽  
Evacuation Simulation ◽  
Multi Agent ◽  
Time Critical ◽  
Mass Evacuation ◽  
Performance Computing

On a Mass Evacuation Simulator with Complex Autonomous Agents and Applications

2016 ◽  
Vol 10 (05) ◽  
pp. 1640021 ◽  
Author(s):  
L Aguilar ◽  
M. L. L. Wijerathne
Keyword(s):  
High Resolution ◽  
High Performance ◽  
Autonomous Agents ◽  
Small Scale ◽  
Agent System ◽  
Complex Agent ◽  
Resolution Model ◽  
Complex Models ◽  
Multi Agent ◽  
Mass Evacuation

This paper presents the details of a mass evacuation simulator with complex autonomous agents on a high resolution model of environment along with demonstrative applications that highlight its usefulness, need and uniqueness. Most of existing mass evacuation simulators are based on simplified models, and the use of complex models is limited to small scale simulations. This simulator makes use of high performance computing to introduce a complex agent system to simulate evacuations in hundreds of square kilometer size domains. The framework of the developed multi-agent system and some of the agents’ constituent functions for interacting with high resolution grid are briefly explained. Interactions are validated using field observations. Two sets of applications are presented to demonstrate the systems use for simulating mixed mode evacuation and evacuation in dynamically changing environment.

MULTI-AGENT APPROACH TO CONTROL SERVICE-ORIENTED HIGH PERFORMANCE COMPUTING

2016 ◽  
pp. 35-41
Author(s):  
I. V. Bychkov ◽  
G. A. Oparin ◽  
A. G. Feoktistov ◽  
V. G. Bogdanova ◽  
I. A. Sidorov ◽  
...  
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Service Oriented ◽  
Multi Agent ◽  
Performance Computing ◽  
Control Service

A survey on parallel and distributed multi-agent systems for high performance computing simulations

2016 ◽  
Vol 22 ◽  
pp. 27-46 ◽  
Author(s):  
Alban Rousset ◽  
Bénédicte Herrmann ◽  
Christophe Lang ◽  
Laurent Philippe
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Performance Computing

AN INFRASTRUCTURE FOR ENGINEERING COOPERATIVE AGENTS

2000 ◽  
Vol 10 (06) ◽  
pp. 681-711 ◽  
Author(s):  
SOE-TSYR YUAN ◽  
ZENG-LUNG WU
Keyword(s):  
Success Factors ◽  
Critical Mass ◽  
Success Factor ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Bottom Up ◽  
Agent Systems ◽  
Cooperative Agents ◽  
Multi Agent

Currently, systems of cooperative agents (multi-agent systems), possessing the capabilities of autonomy, adaptation, and cooperation, are being used in an increasingly wide variety of application areas, and the conversation-based multi-agent system design is the major design for those multi-agent systems. Supposedly, conversation-based multi-agent systems should have been prevailing enough for tackling dynamic aspects of problems in a variety of domains. However, for industries, multi-agent systems are still found to be in the birth stage where they only show their new values in anticipation for further explorations and improvements in order to attract critical mass of users of information executives or software developers. Nevertheless, what are the success factors that can result in a critical mass of multi-agent system designers? This paper shows one possible success factor — an infrastructure for the bottom-up design of multi-agent systems. The bottom-up design makes it possible for agents to be reassembled into multi-agent systems and reused as needed. However, what do we need to successfully support the bottom-up design? This paper is the first attempt to present a tool that fully supports the bottom-up design of multi-agent systems. The tool has three parts. The first part is a wrapper that wraps each agent so that it exempts the designers from the careful detailed deployment of the inter-relationships between cooperation knowledge and task knowledge inside the agent. This wrapper should be independent of the functions of agents. The second part is an environment that can support the wrapper to automate the cooperation process on behalf of agents. The third part is a graphical assembly panel for developers to visually configure wrapped agents residing at different places of the Internet into a working multi-agent system.

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