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Using a learning mechanism in matchmaking process of agents' negotiation in multi-agent systems

机译:在多主体系统中的主体协商配对过程中使用学习机制

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Negotiation between agents is an important aspect of the multi-agent systems' efficiency. The purpose of this paper is to enhance the efficiency of the multi-agent systems by improving the negotiation between agents in such a system. Here, focus is on the matchmaking mechanism of negotiation in which a matchmaker agent is responsible to find a proper server agent in response to a request of a client agent. The matchmaker agent needs to have the complete knowledge about other agents and their responsibilities in all system. This paper at first proposed that the agents can be categorized in fuzzy groups by regarding previous experiences of their performance and it happens by using a learning module in system. Also determining membership function of an agent in groups is considered. So, the matchmaker agent needs to have the knowledge about fuzzy groups of agents, and refer the requests in the base of such knowledge. When the matchmaker wants to pass a message about a request, it selects an a-cut group of that fuzzy group and sends the message to them. This mechanism leads to lesser communication and message passing in the huge and or Web based systems, the lesser communication and message passing through the system will lead to more efficient system.
机译:代理之间的协商是多代理系统效率的重要方面。本文的目的是通过改进这种系统中的代理之间的协商来提高多代理系统的效率。在此,重点放在协商的匹配机制上,在该机制中,匹配器代理负责响应于客户端代理的请求找到合适的服务器代理。媒人代理人需要对其他代理人及其在所有系统中的职责有完整的了解。本文首先提出可以通过考虑代理的先前经验将代理分类为模糊组,并且可以通过使用系统中的学习模块来实现。还考虑确定组中代理的隶属功能。因此,媒人代理需要具有关于代理模糊组的知识,并在这种知识的基础上引用请求。当媒人希望传递有关请求的消息时,它会选择该模糊组的一个剪切组并将其发送给他们。这种机制导致在大型或基于Web的系统中较少的通信和消息传递,而较少的通过系统的通信和消息传递将导致更高效的系统。

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