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Results: 81
Number of items: 81
  • Open Access
    Szymanik, J., & Verbrugge, R. (2019). Tractability and the computational mind. In M. Sprevak, & M. Colombo (Eds.), The Routledge Handbook of the Computational Mind (pp. 339-354). (Routledge Handbooks in Philosophy). Routledge. https://doi.org/10.4324/9781315643670-26
  • Open Access
    van de Pol, I., Steinert-Threlkeld, S., & Szymanik, J. (2019). Complexity and learnability in the explanation of semantic universals of quantifiers. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Creativity + cognition + computation: 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) : Montreal, Canada, 24-27 July 2019 (Vol. 5, pp. 3015-3021). Cognitive Science Society. https://cognitivesciencesociety.org/cogsci-2019/
  • Open Access
    Carcassi, F., Steinert-Threlkeld, S., & Szymanik, J. (2019). The emergence of monotone quantifiers via iterated learning. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Creativity + cognition + computation: 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) : Montreal, Canada, 24-27 July 2019 (Vol. 1, pp. 190-196). Cognitive Science Society. https://cognitivesciencesociety.org/cogsci-2019/
  • Open Access
    Steinert-Threlkeld, S., & Szymanik, J. (2019). Learnability and Semantic Universals. Semantics and Pragmatics, 12, Article 4. https://doi.org/10.3765/sp.12.4
  • Open Access
    Sippel, J., & Szymanik, J. (2018). Monotonicity and the Complexity of Reasoning with Quantifiers. In T. T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Eds.), COGSCI 2018: Changing/Minds : 40th Annual Cognitive Science Society Meeting : Madison, Wisconsin, USA, July 25-28 (Vol. 2, pp. 1074-1079). Cognitive Science Society. https://cogsci.mindmodeling.org/2018/papers/0213/index.html
  • Open Access
    van de Pol, I., van Rooij, I., & Szymanik, J. (2018). Parameterized complexity of theory of mind reasoning in dynamic epistemic logic. Journal of Logic, Language and Information, 27(3), 255-294. https://doi.org/10.1007/s10849-018-9268-4
  • Open Access
    Pezzelle, S., Steinert Threlkeld, S., Bernardi, R., & Szymanik, J. (2018). Some of Them Can be Guessed! Exploring the Effect of Linguistic Context in Predicting Quantifiers. In I. Gurevych, & Y. Miyao (Eds.), ACL 2018 : The 56th Annual Meeting of the Association for Computational Linguistics: proceedings of the conference : July 15-20, 2018, Melbourne, Australia (Vol. 2, pp. 114-119). The Association for Computational Linguistics. https://doi.org/10.18653/v1/P18-2019
  • Open Access
    Zhao, B., van de Pol, I., Raijmakers, M., & Szymanik, J. (2018). Predicting Cognitive Difficulty of the Deductive Mastermind Game with Dynamic Epistemic Logic Models. In T. T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Eds.), COGSCI 2018: Changing/Minds : 40th Annual Cognitive Science Society Meeting : Madison, WisconChanging/Minds : 40th Annual Cognitive Science Society Meeting : Madison, Wiscsin, USA, July 25-28 (Vol. 5, pp. 2789-2794). Cognitive Science Society. https://cogsci.mindmodeling.org/2018/papers/0527/index.html
  • Szymanik, J., & Thorne, C. (2017). Exploring the relation between semantic complexity and quantifier distribution in large corpora. Language Sciences, 60, 80–93. https://doi.org/10.1016/j.langsci.2017.01.006
  • Open Access
    Talmina, N., Kochari, A., & Szymanik, J. (2017). Quantifiers and verification strategies: connecting the dots. In A. Cremers, T. van Gessel, & F. Roelofsen (Eds.), Proceedings of the 21st Amsterdam Colloquium (pp. 465-473). ILLC. https://semanticsarchive.net/Archive/jZiM2FhZ/AC2017-Proceedings.pdf
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