Reducing communication load on contract net by case-based reasoning-eavesdropping for utilizing message leakage

Takuya Ohko, K. Hiraki, Y. Anzai
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引用次数: 3

Abstract

This paper describes communication load reduction on task negotiation with contract net protocol (CNP) for multiple autonomous mobile robots. For controlling multiple robots, CNP is useful, but the broadcast of task announcement messages on CNP tends to consume much communication load. In order to overcome this problem, the authors have developed a system called LEMMING which learns proper addresses for the task announcement messages with case-based reasoning. However, the learning method used in LEMMING sometimes caused inefficient task execution. In this paper, we propose an extension of LEMMING with message interception which enables the system to execute tasks more efficiently by eavesdropping on leaked message.
利用消息泄漏,通过基于案例的推理窃听来减少契约网的通信负荷
本文研究了基于契约网络协议(CNP)的多自主移动机器人任务协商的通信负荷降低问题。对于多机器人的控制,CNP是有用的,但在CNP上广播任务公告消息往往会消耗大量的通信负载。为了克服这个问题,作者开发了一个名为LEMMING的系统,该系统通过基于案例的推理来学习任务公告消息的正确地址。然而,在LEMMING中使用的学习方法有时会导致任务执行效率低下。在本文中,我们提出了一种扩展LEMMING的消息拦截,通过窃听泄漏的消息,使系统能够更有效地执行任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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