Optimal Regression for Reasoning about Knowledge and Actions - Archive ouverte HAL
Communication Dans Un Congrès Année : 2007

Optimal Regression for Reasoning about Knowledge and Actions

Résumé

We show how in the propositional case both Reiter's and Scherl&Levesque's solutions to the frame problem can be modelled in dynamic epistemic logic (DEL), and provide an optimal regression algorithm for the latter. Our method is as follows: we extend Reiter's framework by integrating observation actions and modal operators of knowledge, and encode the resulting formalism in DEL with announcement and assignment operators. By extending Lutz' recent satisfiability-preserving reduction to our logic, we establish optimal decision procedures for both Reiter's and Scherl&Levesque's approaches: satisfiability is NP-complete for one agent, PSPACE-complete for multiple agents and EXPTIME-complete when common knowledge is involved.
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Dates et versions

hal-03516644 , version 1 (07-01-2022)

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  • HAL Id : hal-03516644 , version 1

Citer

Hans Van Ditmarsch, Andreas Herzig, Tiago de Lima. Optimal Regression for Reasoning about Knowledge and Actions. Conference on Artificial Intelligence 2007, AAAI: Association for the Advancement of Artificial Intelligence, Jul 2007, Vancouver, Canada. pp.1070-1075. ⟨hal-03516644⟩
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