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Communication and propagation of action knowledge in multi-agent systems

机译:多主体系统中动作知识的交流和传播

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Multi-agent systems (MASs) do play an important role in the construction of fault tolerant and robust robot systems. One major advantage of MAS is the fact that multiple agents work towards a common goal, having different skills for specificsubtasks. Usually, agents have to use a common description of the actions to be carried out. Since agents can join and leave the MAS at any time, it is important that knowledge acquired by single agents can he transferred or propagated between agents, toensure that knowledge is not lost, in the case that an agent leaves the system. In this paper, techniques will be presented that enable representation of common extendable action knowledge for task solutions in an agent's knowledge base and additionally,algorithms for propagating this knowledge between agents efficiently and with minimum required communication effort.
机译:多智能体系统(MAS)在容错和健壮的机器人系统的构造中确实发挥了重要作用。 MAS的主要优势之一是多个代理朝着一个共同的目标努力,对特定的子任务具有不同的技能。通常,代理必须对要执行的动作使用通用描述。由于代理可以随时加入和离开MAS,因此重要的是,单个代理获取的知识可以在代理之间进行传递或传播,以确保在代理离开系统的情况下不会丢失知识。在本文中,将介绍一些技术,这些技术可以在代理程序的知识库中表示任务解决方案的通用可扩展动作知识,此外,还可以使用最少的通信工作量在代理程序之间高效传播该知识的算法。

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