A New HTN Planning Framework for Agents in Dynamic Environments

Abstract

In a dynamic environment, even if an agent makes a plan to obtain a goal, the environment might change while the agent is executing the plan. In that case, the plan, which was initially valid when it was made, might later become invalid. Furthermore, in the process of replanning, it is necessary to take into account the side effects of actions already executed. Nowadays, HTN planning is becoming popular among agent researchers because its task decomposition algorithm is efficient and suitable for joint planning in multi-agent systems. However, the dynamic replanning algorithm of HTN planning has not yet been established. In order to solve this problem, we have previously presented an agent life cycle that integrates HTN planning, action execution, knowledge updates, and plan modification. In that agent life cycle, the plans are always kept valid according to the most recent knowledge and situation. However, when one plan does not work and the agent starts using an alternative plan, it sometimes undoes some actions that do not have to be undone. The source of this problem lies in the need to have total-order plans. In other words, all the actions have to be sequentially ordered even when the order is not important in some parts of the plan. This paper extends our previous agent life cycle and presents new ways to avoid unnecessary action cancellation. This enables the agent to handle partial-order plans and to make use of two kinds of undoing actions: sequential undoing actions and concurrent undoing actions.