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IJCAI 2007

Conference Paper Knowledge Representation and Reasoning Artificial Intelligence

Abstract

Reversing actions is the following problem: After executing a sequence of actions, which sequence of actions brings the agent back to the state just before this execution (an action reversal). Notably, this problem is different from a vanilla planning problem since the state we have to get back to is in general unknown. It emerges, for example, if an agent needs to find out which action sequences are undoable, and which ones are committed choices. It has applications related to plan execution and monitoring in nondeterministic domains, such as recovering from a failed execution by partially undoing the plan, dynamically switching from one executed plan to another, or restarting plans. We formalize action reversal in a logic-based action1 framework and characterize its computational complexity. Since unsurprisingly, the problem is intractable in general, we present a knowledge compilation approach that constructs offline a reverse plan library for efficient (in some cases, linear time) online computation of action reversals. Our results for the generic framework can be easily applied for expressive action languages such as C+ or K.

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Context

Venue
International Joint Conference on Artificial Intelligence
Archive span
1969-2025
Indexed papers
14525
Paper id
695303117883210382