协作式超信息系统的学习代理

A. Namatame, Y. Tsukamoto
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引用次数: 3

摘要

提出了一种学习智能体模型。演示了该模型如何支持将代理集成到分布式超媒体系统中。研究了多智能体系统中的自组织问题,在多智能体系统中,智能体会主动地从自己的经验中学习。每个智能体都被赋予了不同的连接学习能力,在特定的问题领域中表现,并专门与环境进行交互。每个智能体封装了一组从不同的训练示例中获得的特定知识。讨论了与复合智能体模型和异构智能体模型有关的问题。开发了包含异构和复合学习主体的超媒体信息系统。本应用的目的是在开放的分布式工作站环境下开发分布式智能超媒体信息系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Learning agents for cooperative hyperinformation systems
A model of learning agents is presented. It is shown how this model will support the incorporation of agents into distributed hypermedia systems. The question of self-organization in multi-agent systems in which agents are actively learning from their experience is addressed. Each agent, endowed with a different connectionist learning capability, behaves in a specific problem domain and is specialized to interact with environments. Each agent encapsulates a specific set of knowledge obtained from a different set of training examples. The issues relating to the composite and heterogeneous agent models are discussed. The hypermedia information system incorporating heterogeneous and composite learning agents is developed. The aim of this application is to develop the distributed intelligent hypermedia information system in an open environment of distributed workstations.<>
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