arXiv cs.AI· Paola Rizzo, Hector Munoz-Avila, David W. Aha·· 12 小时前AI 评分20
用 HTN 规划统一实现目标生命周期：一种目标推理智能体架构
Hierarchical Task Network planning in the Goal Lifecycle
AI 导读
研究提出一种目标推理（GR）智能体架构，用 Hierarchical Task Network（HTN）规划统一实现 Goal Lifecycle 流程模型，除常见的 expand 与 re-expand 策略外，还将 HTN 规划用于 formulate 策略，从而支持面向更高层总体目标来构建新目标。
正文
Abstract:Goal reasoning (GR) is the process by which intelligent agents continually reason about the goals they are pursuing, which may lead to goal change, for instance when opportunities arise, or when events cause discrepancies among expected and actual outcomes of actions planned to achieve goals. In this paper we investigate whether Hierarchical Task Network (HTN) planning can provide a uniform implementation of the Goal Lifecycle, a flexible process model for goal reasoning in dynamic environments. The Goal Lifecycle progressively refines goals by adding constraints to them through a series of strategies (e.g., {\it formulate, select, expand}) and uses other strategies (e.g., {\it defer, re-expand, repair}) to resolve the current goal when an event impacts it. We present a novel GR agent architecture that employs HTN planning in this Goal Lifecycle. In addition to using HTN planning for the \textit{expand} and \textit{re-expand} strategies, as is frequently done in GR and planning research, we also use it in the \textit{formulate} strategy, to obtain a uniform planning approach that provides several benefits (e.g., the possibility to formulate new goals in view of achieving higher level overarching goals). We also explain how we use an enhanced HTN action representation to process discrepancies among expected and actual action outcomes that can trigger the transition from one goal to another. Finally, we empirically demonstrate that our GR architecture enables simulated autonomous vehicles to adaptively conduct missions in dynamic environments.
| Comments: | 18 pages, 4 figures. Submitted to Advances in Cognitive Systems |
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.34668 [cs.AI] |
| (or arXiv:2610.34668v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.34668 arXiv-issued DOI via DataCite (pending registration) |
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| Journal reference: | Rizzo, P., Muñoz-Avila, H., and Aha, D. W. (2026). Hierarchical Task Network Planning in the Goal Lifecycle. Proceedings of the Thirteenth Annual Conference on Advances in Cognitive Systems (ACS 2026) |
Submission history
From: Hector Munoz-Avila [view email]
[v1]
Mon, 26 Oct 2026 01:01:22 UTC (375 KB)
来源：arXiv cs.AI · arxiv.org