Qualitative Description and Quantitative Optimization of Tactical Reconnaissance Agents System Organization

DOI

10.1080/18756891.2012.718154How to use a DOI?

Keywords

agent, agent-based modeling and simulation, tactical reconnaissance, system organization, optimization, Markov process

Abstract

In this paper, the problem of qualitative description and quantitative optimization for tactical reconnaissance agents system organization is considered with objective of higher teamwork efficiency and more reasonable task balancing strategies. By analyzing tactical reconnaissance system and its environment, task-(role)-entity agent mapping mechanism and agents in system organization, the system framework is qualitatively described. By transforming the system into an interaction task request-service mechanism queuing system, a Markov chain of system state transition is obtained, since its state transition process in interaction is Markov process and accords with real tactical reconnaissance behaviors. By solving the state transition equations, the inherent relationship of tactical reconnaissance agents is found and the optimized system configuration is obtained. The established simulation demonstration system proves that the proposed approach and model are feasible and effective.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Xiong Li
AU  - Yonglong Chen
AU  - Zhiming Dong
PY  - 2012
DA  - 2012/08/01
TI  - Qualitative Description and Quantitative Optimization of Tactical Reconnaissance Agents System Organization
JO  - International Journal of Computational Intelligence Systems
SP  - 723
EP  - 734
VL  - 5
IS  - 4
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2012.718154
DO  - 10.1080/18756891.2012.718154
ID  - Li2012
ER  -