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Nicolas Riesterer




Address: Cognitive Computation Lab
Institut für Informatik
Albert-Ludwigs-Universität Freiburg
Georges-Köhler-Allee 79
79110 Freiburg, Germany

Building 079, Room 00-018

Tel: +49 761 203-97943


Research Interests

  • Predictive Modelling of Human Reasoning
  • Machine Learning
  • Bayesian Statistics & Modelling

Active Projects

  • The CCOBRA Framework: Online predictive modelling of human reasoning. [github]
  • mptpy: Framework for representing, fitting and optimising Multinomial Process Tree Models in Python. [github]


  • Riesterer N., Brand D., Ragni M. (2018) The Predictive Power of Heuristic Portfolios in Human Syllogistic Reasoning. In: Trollmann F., Turhan AY. (Eds.) KI 2018: Advances in Artificial Intelligence. KI 2018. Lecture Notes in Computer Science, vol 11117. Springer, Cham. [poster][code]
  • Riesterer, N., Brand, D., & Ragni, M. (2018) A Machine Learning Approach for Syllogistic Reasoning. In C. Rothkopf et al. (Eds.), Proceedings of the 14th Biannual Conference of the German Society for Cognitive Science (p. 54). [poster]
  • Ragni, M., Riesterer, N., Khemlani, S., & Johnson-Laird, P. (2018) Individuals become more logical without feedback. In T. Rogers, M. Rau, J. Zhu,& C. Kalish (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 1584–1589).
  • Riesterer, N. & Ragni, M. (2018) The Implications of Guessing Types in Multinomial Processing Tree Models: Conditional Reasoning as an Example. In Proceedings of the 16th International Conference on Cognitive Modeling. [slides]
  • Ragni, M., & Riesterer, N. (2017). The Search for Cognitive Models: Standards and Challenges. Bridging the Gap between Human and Automated Reasoning, 10.
  • Riesterer, N., Becker Asano, C., Hué, J., Dornhege, C., & Nebel, B. (2014). The hybrid agent MARCO. In Proceedings of the 16th International Conference on Multimodal Interaction (pp. 80-81). ACM.
  • Becker-Asano, C., Meneses, E., Riesterer, N., Hué, J., Dornhege, C., & Nebel, B. (2014). The hybrid agent MARCO: a multimodal autonomous robotic chess opponent. In Proceedings of the second international conference on Human-agent interaction (pp. 173-176). ACM.
  • Becker-Asano, C., Riesterer, N., Hué, J., & Nebel, B. Embodiment, emotion, and chess: A system description. New Frontiers in Human-Robot Interaction, 74.