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HOMAN, a learning based negotiation method for holonic multi-agent systems

机译:HOMAN,一种基于学习的整体多智能体系统协商方法

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摘要

Holonic multi-agent systems are a special category of multi-agent systems that best fit to environments with numerous agents and high complexity. Like in general multi-agent systems, the agents in the holonic system may negotiate with each other. These systems have their own characteristics and structure, for which a specific negotiation mechanism is required. This mechanism should be simple, fast and operable in real world applications. It would be better to equip negotiators with a learning method which can efficiently use the available information. The learning method should itself be fast, too. Additionally, this mechanism should match the special characteristics of the holonic multi-agent systems. In this paper, we introduce such a negotiation method. Experimental results demonstrate the efficiency of this new approach.
机译:Holonic多主体系统是多主体系统的特殊类别,最适合具有众多主体和高复杂性的环境。像在一般的多智能体系统中一样,整体系统中的智能体可以相互协商。这些系统具有其自身的特征和结构,为此需要特定的协商机制。该机制应该简单,快速并且在实际应用中可操作。最好为谈判者配备可以有效利用现有信息的学习方法。学习方法本身也应该很快。此外,此机制应与完整的多智能体系统的特殊特征相匹配。在本文中,我们介绍了这种协商方法。实验结果证明了这种新方法的有效性。

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