This paper presents a framework for enforcing penalties on intelligent agents that do not comply with authorization or obligation policies in a changing environment. A framework is proposed to represent and reason about penalties in plans, and an algorithm is proposed to penalize an agent's actions based on their level of compliance with respect to authorization and obligation policies. Being aware of penalties an agent can choose a plan with a minimal total penalty, unless there is an emergency goal like saving a human's life. The paper concludes that this framework can reprimand insubordinate agents.

翻译：本文提出了一种框架，用于在动态环境中对违反授权或义务策略的智能体施加惩罚。该框架旨在表征和推理规划中的惩罚机制，并设计了一种算法，根据智能体行为对授权及义务策略的合规程度实施惩罚。除非存在拯救人类生命等紧急目标，智能体在知悉惩罚规则的情况下可选择总惩罚最小的规划方案。本文结论表明，该框架可有效惩戒违规智能体。