Analysis on Negotiation in Platform-Level Armored Force Combat Entity Agents System
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.
KeywordsMarkov Chain Model Stationary Transition Probability Negotiation Protocol Negotiation Behavior Markov Chain Approach
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