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Alechina, N.A., van Lambalgen, M. (1995) Generalized quantification as substructural logic.technical Report. onbekend (FdL).Report | UvA-DARE
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Alechina, N.A., van Lambalgen, M. (1996) Generalized quantification as substructural logic.Journal of Symbolic Logic, Vol. 61 (pp 1006-1044)Article | https://doi.org/10.2307/2275797 | UvA-DARE
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Alechina, N.A. (1995) On a decidable generalized quantifier logic corresponding to a decidable fragment of first-order logic.Journal of Logic, Language and Information, Vol. 4 (pp 177-189)Article | UvA-DARE
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Alechina, N.A. (1995) Modal quantifiers.Institute for Logic, Language and Computation.Thesis, fully internal | UvA-DARE
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Alechina, N.A. (1995) Logic with Probabilistic Operators.In Proceedings ACCOLADE'94 (pp 121-138)Chapter | UvA-DAREAlechina, N.A. (1995) For All Typical.In Symbolic and Quantitative Approach to reasoning and Uncertainty. Proceedings ECSQARU'95 (pp 1-8). Springer.Chapter | UvA-DAREAlechina, N.A. (1995) Logic with Probabilistic Operators.In Proceedings ACCOLADE'94 (pp 121-138)Chapter | UvA-DAREAlechina, N.A. (1995) For All Typical.In Symbolic and Quantitative Approach to Reasoning and Uncertainty. Proceedings ECSQARU'95 (pp 1-8). Springer.Chapter | UvA-DAREAlexiadou, A., Giannakidou, A. (1999) Specificational pseudoclefts as lists.In Shahin, K. Blake, S. Kim, E.-U. (Eds.), Proceedings of the West Coast Conference on Formal Linguistics (WCCFL) XVII (pp 1-16). CSLI Publications.Conference contribution | UvA-DAREAlhama, R.G., Scha, R.J.H., Zuidema, W. (2014) Rule Learning in Humans and Animals.In Cartmill, E.A. Roberts, S. Lyn, H. Cornish, H. (Eds.), The Evolution of Language: proceedings of the 10th International Conference (EVOLANG10), Vienna, Austria, 14-17 April 2014 (pp 371-372). World Scientific.Conference contribution | https://doi.org/10.1142/9789814603638_0049 | UvA-DAREAlhama, R.G., Scha, R.J.H., Zuidema, W. (2014) Rule Learning in Humans.Poster | http://clin24.inl.nl/talks-posters | UvA-DAREAlhama, R.G., Scha, R.J.H., Zuidema, W. (2015) How should we evaluate models of segmentation in artificial language learning?.In Taatgen, N.A. van Vugt, M.K. Borst, J.P. Mehlhorn, K. (Eds.), Proceedings of ICCM 2015: 13th International Conference on Cognitive Modeling : April 9-11, Groningen, The Netherlands (pp 172-173). University of Groningen.Conference contribution | http://www.cognitive-modeling.com/proceedings/ICCM2015_proceedings.pdf | UvA-DAREAlhama, R.G., Scha, R.J.H., Zuidema, W. (2015) How should we evaluate models of segmentation in artificial language learning?.Poster | UvA-DAREAlhama, R.G., Zuidema, W. (2016) Pre-Wiring and Pre-Training: What does a neural network need to learn truly general identity rules?.In Besold, T.R. Bordes, A. d'Avila Garcez, A. Wayne, G. (Eds.), Proceedings of the Workshop on Cognitive Computation: Integrating neural and symbolic approaches 2016: co-located with the 30th Annual Conference on Neural Information Processing Systems (NIPS 2016) : Barcelona, Spain, December 9, 2016 (CEUR Workshop Proceedings, Vol. 1773). CEUR-WS.Conference contribution | http://ceur-ws.org/Vol-1773/CoCoNIPS_2016_paper4.pdf | UvA-DAREAlhama, R.G., Zuidema, W. (2016) Generalization in Artificial Language Learning: Modelling the Propensity to Generalize.In Korhonen, A. Lenci, A. Murphy, B. Poibeau, T. Villavicencio, A. (Eds.), The 54th Annual Meeting of the Association for Computational Linguistics: proceedings of the 7th Workshop on Cognitive Aspects of Computational Language Learning: August 11, 2016, Berlin, Germany (pp 64-72). Association for Computational Linguistics.Conference contribution | https://doi.org/10.18653/v1/W16-19 | UvA-DAREAlhama, R.G., Zuidema, W. (2017) Segmentation as Retention and Recognition: the R&R model.In Gunzelmann, G. Howes, A. Tenbrink, T. Davelaar, E.J. (Eds.), CogSci 2017: proceedings of the 39th Annual Meeting of the Cognitive Science Society : London, UK : 26-29 July 2017 : Computational Foundations of Cognition (pp 1531-1536). Cognitive Science Society.Conference contribution | https://cogsci.mindmodeling.org/2017/papers/0300/index.html | UvA-DAREAlhama, R.G., Zuidema, W. (2018) Pre-wiring and pre-training: What does a neural network need to learn truly general identity rules?.Journal of Artificial Intelligence Research, Vol. 61 (pp 927-946)Article | https://doi.org/10.1613/jair.1.11197 | UvA-DAREAlhama, R.G., Zuidema, W. (2019) A review of computational models of basic rule learning: The neural-symbolic debate and beyond.Psychonomic Bulletin and Review, Vol. 26 (pp 1174-1194)Review article | https://doi.org/10.3758/s13423-019-01602-z | UvA-DAREAlhama, R.G. (2017) Computational modelling of Artificial Language Learning: Retention, Recognition & Recurrence.Thesis, fully internal | UvA-DAREAliseda-Llera, A. (1997) Seeking Explanations: Abduction in Logic, Philosophy of Science and Artificial Intelligence.Universiteit van Amsterdam.Thesis, fully external | UvA-DARE
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