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  1. Reasoning agents in a dynamic world: The frame problem.Jozsef A. Toth - 1995 - Artificial Intelligence 73 (1-2):323-369.
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  • The Qualification Problem: A solution to the problem of anomalous models.Michael Thielscher - 2001 - Artificial Intelligence 131 (1-2):1-37.
  • Reasoning about actions: steady versus stabilizing state constraints.Michael Thielscher - 1998 - Artificial Intelligence 104 (1-2):339-355.
  • Ramification and causality.Michael Thielscher - 1997 - Artificial Intelligence 89 (1-2):317-364.
  • Motivated action theory: a formal theory of causal reasoning.Lynn Andrea Stein & Leora Morgenstern - 1994 - Artificial Intelligence 71 (1):1-42.
  • The use of dynamics in an intelligent controller for a space faring rescue robot.Marcel Schoppers - 1995 - Artificial Intelligence 73 (1-2):175-230.
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  • Exploiting patterns of interaction to achieve reactive behavior.D. M. Lyons & A. J. Hendriks - 1995 - Artificial Intelligence 73 (1-2):117-148.
  • From the textual description of an accident to its causes.Daniel Kayser & Farid Nouioua - 2009 - Artificial Intelligence 173 (12-13):1154-1193.
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  • M odular- E and the role of elaboration tolerance in solving the qualification problem.Antonis Kakas, Loizos Michael & Rob Miller - 2011 - Artificial Intelligence 175 (1):49-78.
  • Metatheory of Actions: Beyond Consistency.Andreas Herzig & Ivan Varzinczak - 2007 - Artificial Intelligence 171 (1):951–984.
    Traditionally, consistency is the only criterion for the quality of a theory in logic-based approaches to reasoning about actions. This work goes beyond that and contributes to the metatheory of actions by investigating what other properties a good domain description should have. We state some metatheoretical postulates concerning this sore spot. When all postulates are satisfied we call the action theory modular. Besides being easier to understand and more elaboration tolerant in McCarthy’s sense, modular theories have interesting properties. We point (...)
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  • An Epistemic Approach to Nondeterminism: Believing in the Simplest Course of Events.James P. Delgrande & Hector J. Levesque - 2019 - Studia Logica 107 (5):859-886.
    This paper describes an approach for reasoning in a dynamic domain with nondeterministic actions in which an agent’s beliefs correspond to the simplest, or most plausible, course of events consistent with the agent’s observations and beliefs. The account is based on an epistemic extension of the situation calculus, a first-order theory of reasoning about action that accommodates sensing actions. In particular, the account is based on a qualitative theory of nondeterminism. Our position is that for commonsense reasoning, the world is (...)
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  • Learning action models with minimal observability.Diego Aineto, Sergio Jiménez Celorrio & Eva Onaindia - 2019 - Artificial Intelligence 275 (C):104-137.
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