Current Research Project

Publications

  • Context-Based Inferences from Probabilistic Conditionals with Default Negation at Maximum Entropy
    Marco Wilhelm and Gabriele Kern-Isberner
    Proceedings of the 33rd International Florida Artificial Intelligence Research Society Conference (FLAIRS), 2020
  • The Complexity of the Consistency Problem in the Probabilistic Description Logic ALC^ME
    Franz Baader, Andreas Ecke, Gabriele Kern-Isberner, and Marco Wilhelm
    Proceedings of the 12th International Symposium on Frontiers of Combining Systems (FroCoS), 2019
  • Maximum Entropy Calculations for the Probabilistic Description Logic ALC^ME
    Marco Wilhelm and Gabriele Kern-Isberner
    Description Logic, Theory Combination, and All That. Springer, 2019
  • Integrating Typed Model Counting into First-Order Maximum Entropy Computations and the Connection to Markov Logic Networks
    Marco Wilhelm, Gabriele Kern-Isberner, Marc Finthammer, and Christoph Beierle
    Proceedings of the 32nd International Florida Artificial Intelligence Research Society Conference (FLAIRS), 2019
  • Counting Strategies for the Probabilistic Description Logic ALC^ME Under the Principle of Maximum Entropy
    Marco Wilhelm, Gabriele Kern-Isberner, Andreas Ecke, and Franz Baader
    Proceedings of the 16th Edition of the European Conference on Logics in Artificial Intelligence (JELIA), 2019
  • Evaluating Reactive ASP by Formal Belief Revision
    Jonas Philipp Haldimann, Marco Wilhelm, and Gabriele Kern-Isberner
    Workshop on Hybrid Reasoning and Learning (HRL) at the 16th International Conference on Principles of Knowledge Representation and Reasoning (KR), 2018 (unpublished)
  • A Generalized Iterative Scaling Algorithm for Maximum Entropy Model Computations Respecting Probabilistic Independencies
    Marco Wilhelm, Gabriele Kern-Isberner, Marc Finthammer, and Christoph Beierle
    Proceedings of the 10th International Symposium on Foundations of Information and Knowledge Systems (FOIKS), 2018
  • Drawing Inferences Under Maximum Entropy From Relational Probabilistic Knowledge Using Group Theory
    Gabriele Kern-Isberner, Marco Wilhelm, and Christoph Beierle
    Infinite Group Theory: From the Past to the Future. World Scientific, 2018
  • Basic Independence Results for Maximum Entropy Reasoning Based on Relational Conditionals
    Marco Wilhelm, Gabriele Kern-Isberner, and Andreas Ecke.
    Proceedings of the 3rd Global Conference on Artificial Intelligence (GCAI), 2017
  • First-Order Typed Model Counting for Probabilistic Connditional Reasoning at Maximum Entropy
    Marco Wilhelm, Marc Finthammer, Gabriele Kern-Isberner, and Christoph Beierle.
    Proceedings of the 11th International Conference on Scalable Uncertainty Management (SUM), 2017
  • A Semantics for Conditionals with Default Negation
    Marco Wilhelm, Christian Eichhorn, Richard Niland, and Gabriele Kern-Isberner.
    Proceedings of the 14th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU), 2017
  • Typed Model Counting and its Application to Probabilistic Conditional Reasoning at Maximum Entropy
    Marco Wilhelm and Gabriele Kern-Isberner.
    Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference (FLAIRS), 2017
  • Probabilistic knowledge representation using the principle of maximum entropy and Gröbner basis theory
    Gabriele Kern-Isberner, Marco Wilhelm, and Christoph Beierle.
    Annals of Mathematics and Artificial Intelligence 79: pp. 163-179, 2017
  • Propositional Probabilistic Reasoning at Maximum Entropy Modulo Theories
    Marco Wilhelm, Gabriele Kern-Isberner, and Andreas Ecke.
    Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference (FLAIRS), 2016
  • A Novel Methodology for Processing Probabilistic Knowledge Bases Under Maximum Entropy
    Gabriele Kern-Isberner, Marco Wilhelm, and Christoph Beierle.
    Proceedings of the 27th International Florida Artificial Intelligence Research Society Conference (FLAIRS), 2014
  • Probabilistic Knowledge Representation Using Gröbner Basis Theory
    Gabriele Kern-Isberner, Marco Wilhelm, and Christoph Beierle.
    13th International Symposium on Artificial Intelligence and Mathematics (ISAIM), 2014 (unpublished)

Talks

  • Focused Inference and System P
    Journal Club of Working Group Information Engineering, TU Dortmund.
    Dortmund, Germany (July 8, 2020)
  • PRECORE Challenge - Using the Principle of Maximum Entropy to Predict Human Responses to Syllogism Tasks
    41st Cognitive Science Conference (CogSci 2019).
    Montreal, Canada (July 24, 2019)
  • Probabilistic Inferences Under Maximum Entropy for Description Logics
    Journal Club of Working Group Information Engineering, TU Dortmund.
    Dortmund, Germany (July 17, 2019)
  • PRECORE Challenge - Using the Principle of Maximum Entropy to Predict Human Responses to Syllogism Tasks
    Journal Club of Working Group Information Engineering, TU Dortmund.
    Dortmund, Germany (June 27, 2019)
  • Probabilistic Description Logics Based on the Aggregating Semantics and the Principle of Maximum Entropy
    13th Workshop on Hybrid Reasoning of DFG Research Unit 1513.
    Berlin, Germany (June 21, 2019)
  • The Probabilistic Description Logic ALC^ME
    34th Miniworkshop on Theoretical Computer Science, TU Dortmund.
    Dortmund, Germany (May 27, 2019)
  • Counting Strategies for the Probabilistic Description Logic ALC^ME Under the Principle of Maximum Entropy
    16th Edition of the European Conference on Logics in Artificial Intelligence (JELIA 2019).
    Rende, Italy (May 8, 2019)
  • A Semantics for Conditionals with Default Negation
    3rd Workshop on Human Reasoning and Computational Logic.
    Dresden, Germany (April 5, 2019)
  • ALC^ME - A Probabilistic Description Logic Under the Aggregating Semantics and the Principle of Maximum Entropy
    Joint Doctoral Colloquium of Working Groups Wissensbasierte Systeme, FernUniversität Hagen, and Information Engineering, TU Dortmund.
    Hagen, Germany (December 19, 2018)
  • ALC^ME - A Probabilistic Description Logic Under the Aggregating Semantics and the Principle of Maximum Entropy
    12th Workshop on Hybrid Reasoning of DFG Research Unit 1513.
    Freiburg im Breisgau, Germany (November 13, 2018)
  • Typed Model Counting
    Journal Club of Working Group Information Engineering, TU Dortmund.
    Dortmund, Germany (July 9, 2018)
  • A Generalized Iterative Scaling Algorithm for Maximum Entropy Model Computations Respecting Probabilistic Independencies
    10th International Symposium on Foundations of Information and Knowledge Systems (FOIKS 2018).
    Budapest, Hungary (May 16, 2018)
  • Improving an Iterative Scaling Algorithm for Computing First-order Maximum Entropy Distributions
    11th Workshop on Hybrid Reasoning of DFG Research Unit 1513.
    Potsdam, Germany (May 8, 2018)
  • A Generalized Iterative Scaling Algorithm for Maximum Entropy Model Computations Respecting Probabilistic Independencies
    Journal Club of Working Group Information Engineering, TU Dortmund.
    Dortmund, Germany (April 30, 2018)
  • (First-order) Typed Model Counting for Maximum Entropy Reasoning
    Joint Doctoral Colloquium of Working Groups Wissensbasierte Systeme, FernUniversität Hagen, and Information Engineering, TU Dortmund.
    Hagen, Germany (December 19, 2017)
  • First-Order Typed Model Counting for Probabilistic Conditional Reasoning at Maximum Entropy
    11th International Conference on Scalable Uncertainty Management (SUM 2017).
    Granada, Spain (October 6, 2017)
  • Typed Model Counting and its Application to Probabilistic Conditional Reasoning at Maximum Entropy
    30th International Conference of the Florida Artificial Intelligence Research Society (FLAIRS 2017).
    Marco Island, Florida, USA (May 23, 2017)
  • A Semantics for Conditionals with Default Negation
    Journal Club of Working Group Information Engineering, TU Dortmund.
    Dortmund, Germany (May 3, 2017)
  • Typed Model Counting and its Application to Probabilistic Conditional Reasoning at Maximum Entropy
    Joint Doctoral Colloquium of Working Groups Wissensbasierte Systeme, FernUniversität Hagen, and Information Engineering, TU Dortmund.
    Hagen, Germany (December 21, 2016)
  • Typed Model Counting and its Application to Probabilistic Conditional Reasoning at Maximum Entropy
    8th Workshop on Hybrid Reasoning of DFG Research Unit 1513.
    Dresden, Germany (November 29, 2016)
  • Typed Model Counting and its Application to Probabilistic Conditional Reasoning at Maximum Entropy
    Journal Club of Working Group Information Engineering, TU Dortmund.
    Dortmund, Germany (August 24, 2016)
  • CondStructor - An Algorithm for Classifying Possible Worlds With a View to Probabilistic Reasoning at Maximum Entropy
    7th Workshop on Hybrid Reasoning of DFG Research Unit 1513.
    Freiburg im Breisgau, Germany (June 6, 2016)
  • Probabilistic Inferences under Maximum Entropy for Description Logics. Building Equivalence Classes of Possible Worlds With Respect to Conditional Knowledge

    Joint Doctoral Colloquium of Working Groups Wissensbasierte Systeme, FernUniversität Hagen, and Information Engineering, TU Dortmund.
    Hagen, Germany (December 16, 2015)

  • Probabilistic Knowledge Representation Using Gröbner Basis Theory
    13th International Symposium on Artificial Intelligence and Mathematics (ISAIM 2014).
    Fort Lauderdale, Florida, USA (January 8, 2014)
  • Probabilistic Knowledge Representation Using Gröbner Basis Theory
    23th Miniworkshop on Theoretical Computer Science, TU Dortmund.
    Dortmund, Germany (June 24, 2013)
  • Probabilistic Knowledge Representation Using Gröbner Basis Theory
    Journal Club of Working Group Information Engineering, TU Dortmund.
    Dortmund, Germany (June 11, 2013)

Activities

Misc