用多智能体技术增强传统搜索系统:一个案例研究

J. Denzinger, Dirk Fuchs
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引用次数: 8

摘要

我们的TECHS概念(TEams for Cooperative Heterogeneous Search)是针对不同搜索系统之间的合作。因此,搜索代理是一个具有固定参数设置的顺序搜索系统。在一个代理团队中,多个代理可能使用相同的搜索系统,但它们必须使用不同的参数。与大多数其他方法不同,要解决的问题没有划分成子问题,然后再交给搜索代理。相反,所有代理都得到整个问题。例外情况只适用于不能“理解”整个问题的代理。他们只得到他们能处理的部分。因此,我们可以在团队中使用现有的顺序搜索系统。在TECHS中,搜索代理之间的数据交换既是需求驱动的,也是成功驱动的。需求驱动合作的特点是,代理计算数据模式,这些模式将帮助它们完成搜索任务,并将这些模式作为请求发送给其他代理。然后,其他代理将所有与模式匹配的数据(可能是由请求触发的额外计算的结果)发送回请求代理。请注意,在搜索系统中,很难找到可以确定代理需要哪些数据来推进或完成搜索任务的标准。成功驱动数据交换的一般思想是,代理确定到目前为止对其搜索非常有用的数据,并定期与同事共享此数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing conventional search systems with multi-agent techniques: a case study
Our TECHS concept (TEams for Cooperative Heterogeneous Search) is aimed at the cooperation of different search systems. Therefore, a search agent is a sequential search system with a fixed setting of its parameters. In a team of agents, several agents might use the same search system but then they must employ different parameters. In contrast to most other approaches the problem to solve is not partitioned into subproblems that are then given to the search agents. Instead, all agents obtain the whole problem. Exceptions are only made for agents that cannot "understand" the whole problem. They only get the parts they can work on. Thus, we can use existing sequential search systems in our teams. The data interchange between search agents in TECHS is both demand driven and success driven. Demand driven cooperation is characterized by agents computing patterns of data that would help them fulfil their search task and send these patterns as requests to other agents. The other agents then send all their data matching the patterns (that may be the result of additional computations triggered by the request) back to the requesting agent. Note that in search systems it is rather difficult to find criteria that can determine which data an agent needs to advance or finish a search task. The general idea of success driven data interchange is that an agent determines the data that was, so far, very useful for its search and periodically shares this data with its colleagues.
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