让智能体在安全或个性约束下自主决策，不盲目执行指令。
R-HTN: Rebellious Online HTN Planning for Safety and Game AI
- 基于指令集 \\D 构建在线层次任务网络规划器，支持叛逆行为。
- 两类智能体：非自适应型直接停止违规任务，自适应型主动重构计划。
- 适用于需要安全约束或个性化行为的游戏与机器人系统。
我们提出一种基于内置指令集 \D 的在线层次任务网络（HTN）智能体，其行为可在特定条件下拒绝执行用户任务，表现出‘智能违抗’。该工作融合了HTN规划、在线规划与指令集 \D 三者，设计了两种代理变体：(1) 非自适应型，在发现违反 \D 时立即停止执行；(2) 自适应型，在相同情境下主动修改HTN计划，寻找替代路径完成目标。我们提出R-HTN（Rebellious-HTN）算法，用于在指令 \D 约束下的在线HTN规划。在两个任务领域中评估，要求智能体因安全或个性特征不得违反某些指令。实验表明，R-HTN智能体始终不违反指令，且在可行前提下努力达成用户目标，尽管方式可能不符合用户预期。
原文摘要 · Abstract (English)
We introduce online Hierarchical Task Network (HTN) agents whose behaviors are governed by a set of built-in directives \D. Like other agents that are capable of rebellion (i.e., {\it intelligent disobedience}), our agents will, under some conditions, not perform a user-assigned task and instead act in ways that do not meet a user's expectations. Our work combines three concepts: HTN planning, online planning, and the directives \D, which must be considered when performing user-assigned tasks. We investigate two agent variants: (1) a Nonadaptive agent that stops execution if it finds itself in violation of \D~ and (2) an Adaptive agent that, in the same situation, instead modifies its HTN plan to search for alternative ways to achieve its given task. We present R-HTN (for: Rebellious-HTN), a general algorithm for online HTN planning under directives \D. We evaluate R-HTN in two task domains where the agent must not violate some directives for safety reasons or as dictated by their personality traits. We found that R-HTN agents never violate directives, and aim to achieve the user-given goals if feasible though not necessarily as the user expected.
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