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Nicolas Riesterer

 

 

Nicolas

Address: Cognitive Computation Lab
Institut für Informatik
Albert-Ludwigs-Universität Freiburg
Georges-Köhler-Allee 52
79110 Freiburg, Germany
Room:

Building 052, Room 00-045

Tel: +49 761 203-8232
Email:
Github:

https://github.com/nriesterer

RGate:

https://www.researchgate.net/profile/Nicolas_Riesterer

 

Research Interests

  • Predictive Modelling of Human Reasoning
  • Machine Learning
  • Information Systems & Modelling

Active Projects

  • The CCOBRA Framework: Online predictive modelling of human reasoning. [github][website]
  • pymreasoner: Python interface for the Lisp-based cognitive model for human syllogistic reasoning mReasoner. [github]

Past Projects

  • mptpy: Framework for representing, fitting and optimising Multinomial Process Tree Models in Python. [github]

Teaching

Publications

  • Brand, D., Riesterer, N., & Ragni, M. (2019). On the Matter of Aggregate Models for Syllogistic Reasoning: A Transitive Set-Based Account for Predicting the Population. In Stewart T. (Ed.), Proceedings of the 17th International Conference on Cognitive Modeling. [pdf][slides][code]
  • Riesterer, N., Brand, D., & Ragni, M. (2019). Predictive Modeling of Individual Human Cognition: Upper Bounds and a New Perspective on Performance. In Stewart T. (Ed.), Proceedings of the 17th International Conference on Cognitive Modeling. [pdf][slides][code]
  • Riesterer, N., Brand, D., Dames, H., & Ragni, M. (2019). Modeling Human Syllogistic Reasoning: The Role of "No Valid Conclusion", In Goel, A., Seifert, C., & Freska, C. (Eds.), Proceedings of the 41st Annual Conference of the Cognitive Science Society. [pdf][slides][code]
  • Ragni, M., Dames, H., Brand, D., & Riesterer, N. (2019). When Does a Reasoner Respond: Nothing Follows?, In Goel, A., Seifert, C., & Freska, C. (Eds.), Proceedings of the 41st Annual Conference of the Cognitive Science Society.
  • 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 (pp. 415-421). [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. 2315-2320).
  • Dames, H., von Hartz, J. O., Kantz, M., Riesterer, N., & Ragni, M. (2018). Multinomial processing models for syllogistic reasoning: A comparison. 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 I. Juvina, J. Houpt, & C. Myers (Eds.), Proceedings of the 16th International Conference on Cognitive Modeling (pp. 114-119). [pdf][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. (2015). Embodiment, emotion, and chess: A system description. New Frontiers in Human-Robot Interaction, 74.

Talks

  • 2019, July (CogSci, Montréal, QB): Modeling Human Syllogistic Reasoning: The Role of "No Valid Conclusion" [slides]
  • 2019, July (CogSci, Montréal, QB): CCOBRA and the PRECORE Modeling Challenge (part of the "Predicting Individual Human Reasoning: The PRECORE-Challenge" workshop) [slides]
  • 2019, July (ICCM, Montréal, QB): Predictive Modeling of Individual Human Cognition: Upper Bounds and a New Perspective on Performance [slides]
  • 2019, April (WHRCL, Dresden): The CCOBRA Framework for Benchmarking Cognitive Models [slides]
  • 2018, July (ICCM, Madison, WI): The Implications of Guessing Types in Multinomial Processing Tree Models: Conditional Reasoning as an Example [slides]
  • 2017, February (WHRCL, Dresden): Evaluating Cognitive Theories using MPTs [slides]