KR2020Proceedings of the 17th International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning

Rhodes, Greece. September 12-18, 2020.

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Copyright © 2020 International Joint Conferences on Artificial Intelligence Organization

On the Reversibility of Actions in Planning

  1. Michael Morak(University of Klagenfurt, Austria)
  2. Lukas Chrpa(Czech Technical University, Prague, Czech Republic)
  3. Wolfgang Faber(University of Klagenfurt, Austria)
  4. Daniel Fišer(Czech Technical University, Prague, Czech Republic)

Keywords

  1. Reasoning about actions and change, action languages-General

Abstract

Checking whether action effects can be undone is an important question for determining, for instance, whether a planning task has dead-ends. In this paper, we investigate the reversibility of actions, that is, when the effects of an action can be reverted by applying other actions, in order to return to the original state. We propose a broad notion of reversibility that generalizes previously defined versions and investigate interesting properties and relevant restrictions. In particular, we propose the concept of uniform reversibility that guarantees that an action can be reverted independently of the state in which the action was applied, using a so-called reverse plan. In addition, we perform an in-depth investigation of the computational complexity of deciding action reversibility. We show that reversibility checking with polynomial-length reverse plans is harder than polynomial-length planning and that, in case of unrestricted plan length, the PSPACE-hardness of planning is inherited. In order to deal with the high complexity of solving these tasks, we then propose several incomplete algorithms that may be used to compute reverse plans for a relevant subset of states.