在基于知识库的智能体框架上设计学习智能体的支持机制

Sho Itazuro, Takahiro Uchiya, I. Takumi, Tetsuo Kinoshita
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引用次数: 0

摘要

面向智能体的计算是一种根据行为知识生成自主操作的智能体的技术。此外,智能体可以具有一种称为“学习”技能的特征。通过实现“学习”技能,可以期望agent更高效的运行。在本研究中,我们的目标是支持智能体设计者设计并开发具有“学习”技能的智能体。我们在基于存储库的代理框架DASH框架上提出了一种学习代理的设计支持机制。所提出的机制使智能体设计者无需专业知识即可设计和实现学习智能体,从而减轻了设计者的负担。在这里,我们解释了DASH框架、Q-Learning和提出的设计支持机制。最后,通过实验验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design support mechanism of learning agent on repository-based agent framework
Agent-oriented computing is a technique for generating an agent that operates autonomously according to behavior knowledge. Moreover, an agent can have a characteristic called “Learning” skill. More efficient operation of an agent can be expected by realizing “Learning” skill. In this research, our aim is to support an agent designer who designs and develops an agent equipped with “Learning” skill. We propose a design support mechanism of a learning agent on a repository-based agent framework called the DASH framework. The proposed mechanism enables an agent designer to design and implement the learning agent without great expertise, thereby reducing the designer's burden. Herein, we explain the DASH framework, Q-Learning, and the proposed design support mechanism. Moreover, we demonstrate the effectiveness of the proposed method using some experiments.
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