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摘要翻译：
本文将层次任务网络(HTNs)所描述的过程控制知识与丰富的定性用户偏好相结合，解决了生成偏好计划的问题。我们的工作成果是一种用于指定用户偏好的语言，为HTN规划量身定制，以及一个可证明的最优的基于偏好的规划器HTNPLAN，它是作为Shop2的扩展实现的。为了计算优选方案，我们提出了一种基于前向链启发式搜索的方法。我们的启发式使用一个可接受的评价函数来衡量偏好对部分计划的满意度。我们的经验评估证明了我们的HTNPLAN启发式的有效性。我们通过调用情景演算、偏好语言的语义和HTN规划来证明我们的方法是合理的和最优的。虽然我们的实现构建在SHOP2之上，但这里提出的语言和技术与HTN规划者的范围非常广泛。
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英文标题：
《On Planning with Preferences in HTN》
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作者：
Shirin Sohrabi and Sheila A. McIlraith
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最新提交年份：
2009
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
In this paper, we address the problem of generating preferred plans by combining the procedural control knowledge specified by Hierarchical Task Networks (HTNs) with rich qualitative user preferences. The outcome of our work is a language for specifyin user preferences, tailored to HTN planning, together with a provably optimal preference-based planner, HTNPLAN, that is implemented as an extension of SHOP2. To compute preferred plans, we propose an approach based on forward-chaining heuristic search. Our heuristic uses an admissible evaluation function measuring the satisfaction of preferences over partial plans. Our empirical evaluation demonstrates the effectiveness of our HTNPLAN heuristics. We prove our approach sound and optimal with respect to the plans it generates by appealing to a situation calculus semantics of our preference language and of HTN planning. While our implementation builds on SHOP2, the language and techniques proposed here are relevant to a broad range of HTN planners.
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PDF链接：
https://arxiv.org/pdf/0909.0682
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