提高用户模型开发效率

Geoffrey P. Morgan, S. Haynes, Frank E. Ritter, Mark A Cohen
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引用次数: 15

摘要

本文介绍了草本语言,这是一种用于创建人工智能代理和认知模型的高级行为表示语言。它描述了来自其他高级建模语言的经验教训,这些经验教训为草本的设计提供了指导,并将为其他高级行为表示语言提供指导。我们描述了在Herbal中构建的一个模型来说明它的使用和应用。本文的结论是,像Herbal这样的语言可以帮助解释智能代理和认知模型的设计意图,并使它们更容易创建、修改和理解。这些结果在模型重用大量自身结构的情况下显得尤其正确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Increasing efficiency of the development of user models
This paper introduces Herbal, a high-level behavior representation language for creating AI agents and cognitive models. It describes the lessons from other high-level modeling languages that informed the design of Herbal and that will inform other high-level behavior representation languages. We describe a model built in Herbal to illustrate its use and application. The paper concludes that languages like Herbal can help explain the design intent of intelligent agents and cognitive models, and make them easier to create, modify, and understand. These results appear to be particularly true where the model reuses a lot of its own structures.
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