设计一个工具,允许在计划识别挑战和应用程序期间进行更新

R. Cohen, B. Spencer, Patrick M. Hoyt
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引用次数: 3

摘要

传统上,计划识别被定义为将用户的一组观察结果与域内可能的计划库进行匹配的过程,表明用户可能的候选计划。我们开发了一个系统,该系统允许在计划识别期间更新计划库,并修改候选计划列表,而无需重新启动计划识别过程。这项工作建立在H. Kautz的计划识别模型(1987)的基础上,并应用了真值维持。我们描述了我们为系统用户开发的一个面向图形的工具。我们评论我们所获得的见解,关于用户类型和我们可能想要适应的修改类型。我们强调系统的重要性,允许不完整或不正确的库进行修改。我们总结了界面设计和规划识别方面仍然存在的挑战。最后,我们详细阐述了我们的系统在各种人工智能应用中的潜在用途,包括基于知识的系统、协作人工智能和自然语言理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing a tool to allow updates during plan recognition-challenges and applications
Traditionally, plan recognition is defined as the process of matching a set of observations from a user to a library of possible plans in a domain, indicating the possible candidate plans of the user. We have developed a system which allows updates to the plan library during plan recognition and which amends the list of candidate plans, without having to restart the plan recognition process. This work builds on H. Kautz's model (1987) of plan recognition and applies truth maintenance. We describe a graphic-oriented tool which we have developed for users of our system. We comment on the insights which we have gained, about the kinds of users and the kinds of modifications which we might want to accommodate. We emphasize the significance of the system, allowing incomplete or incorrect libraries to be amended. We summarize the challenges which remain, both for interface design and plan recognition. Finally, we elaborate on the potential use of our system for a variety of artificial intelligence applications including knowledge based systems, cooperative AI and natural language understanding.<>
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