Abstract
The ramification problem in Artificial Intelligence is concerned with the indirect effects of an action. It has been shown in previous work that the ramification problem can be solved with the use of integrity constraints and actions representation. In this paper we begin with a quick review of the existing Description Logic Languages, and then we describe a Temporal Extension of Description Logics, able to represent integrity constraints, temporalized actions and non persistent effects. We describe a thorough solution to the ramification problem in Temporal Settings expressed in Temporal Description Logics. The solution also deals with the hard case, in which the effects of an action change the belief about the past.
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