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Analysis on Negotiation in Platform-Level Armored Force Combat Entity Agents System

  • Xiong Li
  • Kai Wang
  • Xianggang Liu
  • Jiuting Duo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

In this paper we present a platform-level simulation architecture for tactical armored force combat entity agents system by setting up mappings from combat entities to respective combat entity agents. In order to solve the problems on negotiation to enhance overall system efficiency, based on qualitative description of its framework, we place particular emphasis on quantitative analysis. Through transforming the system into a series-wound queueing system, we attain a Markov chain of stationary transition probabilities, since its stationary transition process in negotiation is a discrete state Markov process and accords with real military combat behaviors. Solving the stationary transition equations makes us find high-efficiency negotiation according to optimized system configuration. The obtained results show the effectiveness of the proposed approach and model.

Keywords

Markov Chain Model Stationary Transition Probability Negotiation Protocol Negotiation Behavior Markov Chain Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiong Li
    • 1
  • Kai Wang
    • 1
  • Xianggang Liu
    • 1
  • Jiuting Duo
    • 1
  1. 1.Department of Command and Administration, Academy of Armored Force Engineering, Beijing 100072China

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