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IDEAL: Interactive design environment for agent system with learning mechanism

机译:理想:具有学习机制的代理系统的交互式设计环境

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The agent-oriented computing is a technique for generating the agent who operates autonomously according to the behavior knowledge. Moreover, agent can have the characteristic called “Learning” skill. More efficient operation of agents can be expected by realizing “Learning” skill. In this research, our aim is to support agent designer who designs and develops the intelligent agent system equipped with “Learning” skill. We propose interactive design environment for agent system with learning mechanism using repository-based agent framework called DASH framework. Proposed framework enables agent designer to design and implement the learning agents without highly expertise, therefore we can reduce the designer's burden. In this paper, we explain the DASH framework, Q-learning, Profit Sharing and proposed design environment. Moreover we show the effectiveness of the proposal method through the some experiments.
机译:面向代理的计算是一种用于生成根据行为知识自主运行的代理的技术。而且,代理人可以具有称为“学习”技能的特征。通过实现“学习”技能,可以期望代理更有效地操作。在这项研究中,我们的目的是支持代理设计师,他们设计和开发具有“学习”技能的智能代理系统。我们使用称为DASH框架的基于存储库的代理框架,为具有学习机制的代理系统提供交互式设计环境。拟议的框架使代理设计人员无需高度专业知识即可设计和实施学习型代理,因此我们可以减轻设计人员的负担。在本文中,我们解释了DASH框架,Q学习,利润共享和拟议的设计环境。此外,通过一些实验,我们证明了该建议方法的有效性。

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