
A framework for assessing systematically theories of action and change is presented. The framework consists of a logic for representing scenario descriptions and the semantic machinery for defining the intended models for the descriptions. A proposed theory of action and change is analyzed in terms of its selection function that maps scenario descriptions to sets of models. An assessment of a theory consists of identifying the range of correct applicability of the theory, i.e., identifying the class of scenario descriptions for which the selection function of the theory gives exactly the intended models for each description in the class. For the assessments and comparisons of different theories of action a taxonomy of scenario descriptions is provided whereby the ranges of applicability are specified. The article presents assessment results concerning the case where a logic with explicit integer time is used for scenario descriptions and where strict inertia (simple persistence without, e.g., surprises or ramifications) is assumed. The range of applicability of a number of previously proposed and new theories of action and change based on preferential semantics is examined. The research has been continued and the results have been extended and generalized in a new book of the author's [Features and fluents (Oxford University Press) (1994)].
Logic in artificial intelligence, assessment, nonmonotonic logic, persistence, Other nonclassical logic, frame problem, logic for representing scenario descriptions, intended models, logics of action and change, strict inertia
Logic in artificial intelligence, assessment, nonmonotonic logic, persistence, Other nonclassical logic, frame problem, logic for representing scenario descriptions, intended models, logics of action and change, strict inertia
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