16 found
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  1.  2
    Game Description Language and Dynamic Epistemic Logic Compared.Thorsten Engesser, Robert Mattmüller, Bernhard Nebel & Michael Thielscher - 2021 - Artificial Intelligence 292:103433.
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  2.  15
    Representing and Reasoning About Game Strategies.Dongmo Zhang & Michael Thielscher - 2015 - Journal of Philosophical Logic 44 (2):203-236.
    As a contribution to the challenge of building game-playing AI systems, we develop and analyse a formal language for representing and reasoning about strategies. Our logical language builds on the existing general Game Description Language and extends it by a standard modality for linear time along with two dual connectives to express preferences when combining strategies. The semantics of the language is provided by a standard state-transition model. As such, problems that require reasoning about games can be solved by the (...)
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  3.  3
    Representing Concurrent Actions and Solving Conflicts.Sven-Erik Bornscheuer & Michael Thielscher - 1996 - Logic Journal of the IGPL 4 (3):355-368.
    As an extension of the well-known Action Description Language A introduced by M. Gelfond and V. Lifschitz [8] C. Baral and M. Gelfond recently defined the diafect AC which supports the description of concurrent actions [1]. Also, a sound but incomplete encoding of AC by means of an extended logic program was presented there. In this paper, we work on interpretations of contradictory inferences from partial action descriptions. Employing an interpretation different from the one implicitly used in AC, we present (...)
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  4. Proceedings of the Sixteenth International Conference on Principles of Knowledge Representation and Reasoning (KR2018).Michael Thielscher, Francesca Toni & Frank Wolter (eds.) - 2018
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  5. Automated Verification of State Sequence Invariants in General Game Playing.Sebastian Haufe, Stephan Schiffel & Michael Thielscher - 2012 - Artificial Intelligence 187:1-30.
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  6. Iterated Belief Revision, Revised.Yi Jin & Michael Thielscher - 2007 - Artificial Intelligence 171 (1):1-18.
  7.  15
    Logical-Epistemic Foundations of General Game Descriptions.Ji Ruan & Michael Thielscher - 2014 - Studia Logica 102 (2):321-338.
    A general game player automatically learns to play arbitrary new games solely by being told their rules. For this purpose games are specified in the general Game Description Language (GDL), a variant of Datalog with function symbols that uses a few game-specific keywords. A recent extension of basic GDL allows the description of nondeterministic games with any number of players who may have incomplete, asymmetric information. In this paper, we analyse the epistemic structure and expressiveness of this language in terms (...)
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  8.  2
    A General First-Order Solution to the Ramification Problem with Cycles.Hannes Strass & Michael Thielscher - 2013 - Journal of Applied Logic 11 (3):289-308.
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  9. A Unifying Action Calculus.Michael Thielscher - 2011 - Artificial Intelligence 175 (1):120-141.
  10. Challenges for Action Theories.Michael Thielscher - 2000
  11. From Situation Calculus to Fluent Calculus: State Update Axioms as a Solution to the Inferential Frame Problem.Michael Thielscher - 1999 - Artificial Intelligence 111 (1-2):277-299.
  12.  20
    Logic-Based Agents and the Frame Problem: A Case for Progression.Michael Thielscher - 2004 - In Vincent F. Hendricks (ed.), First-Order Logic Revisited. Logos. pp. 75--323.
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  13. On Prediction in Theorist.Michael Thielscher - 1993 - Artificial Intelligence 60 (2):283-292.
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  14. Reasoning About Actions: Steady Versus Stabilizing State Constraints.Michael Thielscher - 1998 - Artificial Intelligence 104 (1-2):339-355.
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  15. Ramification and Causality.Michael Thielscher - 1997 - Artificial Intelligence 89 (1-2):317-364.
  16. The Qualification Problem: A Solution to the Problem of Anomalous Models.Michael Thielscher - 2001 - Artificial Intelligence 131 (1-2):1-37.