A major challenge for a medical simulation is to coordinate multiple complex interrelated tasks. Hierarchical Task Networks (HTNs) extend GOAP with team-based strategies to avoid these problems.  Planning problems are specified in the hierarchical task network approach by providing a set of tasks, which can be primitive tasks, which roughly correspond to the actions found in GOAP; compound tasks, which can be seen as composed of a set of simpler tasks, or goal tasks, which roughly corresponds to the goals of GOAP but are more general. A primitive task is a single action that can be executed. A compound task is a sequence of actions. A goal task is a task of satisfying a condition. By working at the higher level of compound tasks, an HTN system understands how common goals are planned to be achieved across multiple agents. HTN’s have been incorporated in military planning and could aid in modeling simulation strategies . A cousin of HTN is the basis for the AI used in Clash of Civilizations.