  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.
