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Performance Improvement of the Contract Net Protocol Using Instance Based Learning

机译:基于实例的学习合同网络协议的性能改进

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The contract net protocol (CNP) is a widely used coordination mechanism in multiagent systems. It has been shown that its performance degrades drastically when the number of communicating agents and the number of tasks announced increases. Hence it has problems of scalability. In order to overcome this limitation, an Instance Based Learning (IBL) mechanism is incorporated with CNP that avoids the expensive bidding process and uses previously stored instances to select a target agent. The scheme is implemented in a simulated distributed hospital system where the CNP is used for resource sharing across hospitals. Experimental results demonstrate that with the incorporation of the IBL, the system performance improves significantly.
机译:合同净协议(CNP)是多元素系统中广泛使用的协调机制。已经表明,当通信代理的数量和宣布增加的任务数量增加时,其性能急剧下降。因此它存在可扩展性问题。为了克服这种限制,基于实例的学习(IBL)机制被包含在CNP中,该CNP避免了昂贵的竞标过程,并使用先前存储的实例来选择目标代理。该方案是在模拟分布式医院系统中实现的,其中CNP用于跨医院的资源共享。实验结果表明,随着IBL的加入,系统性能显着提高。

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