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Creators/Authors contains: "Loc Pham, Enrico Pontelli"

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  1. (, International Conference on Logic Programming)
    null (Ed.)
    This paper introduces a combination of regression and belief revision to allow agents to deal with inconsistencies while executing plans. Starting from an inconsistent history consisting of actions and observations, the proposed framework (1) computes the initial belief states that support the actions and observations and (2) uses a belief revision operator to repair the false initial belief state. The framework operates on domains with static causal laws and supports arbitrary sequences of actions. The paper illustrates how logic programming can be effectively used to support these processes. 
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    Accepted Manuscript Full Text Available