Abstraction of Nondeterministic Situation Calculus Action Theories
Abstraction of Nondeterministic Situation Calculus Action Theories
Bita Banihashemi, Giuseppe De Giacomo, Yves Lesperance
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
Main Track. Pages 3112-3122.
https://doi.org/10.24963/ijcai.2023/347
We develop a general framework for abstracting the behavior of an agent that operates in a nondeterministic domain, i.e., where the agent does not control
the outcome of the nondeterministic actions, based on the nondeterministic situation calculus and the ConGolog programming language. We assume that
we have both an abstract and a concrete nondeterministic basic action theory, and a refinement mapping which specifies how abstract actions, decomposed into agent actions and environment reactions, are implemented by concrete ConGolog programs. This new setting supports strategic reasoning and strategy synthesis, by allowing us to quantify separately on agent actions and environment reactions. We show that if the agent has a (strong FOND) plan/strategy to achieve a goal/complete a task at the abstract level, and it can always execute the nondeterministic abstract actions to completion at the concrete level, then there exist a refinement of it that is a (strong FOND) plan/strategy to achieve the refinement of the goal/task at the concrete level.
Keywords:
Knowledge Representation and Reasoning: KRR: Reasoning about actions
Agent-based and Multi-agent Systems: MAS: Agent theories and models