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  • Alechina, N. A., & van Lambalgen, M. (1995). Generalized quantification as substructural logic. (Technical Report; No. ML-95-05). onbekend (FdL). >>>
  • Alechina, N. A., & van Lambalgen, M. (1995). Generalized quantification as substructural logic. (technical Report; No. ML-95-05). onbekend (FdL). >>>
  • Alechina, N. A., & van Lambalgen, M. (1995). Correspondence and Completeness for Generalized Quantifiers. Logic Journal of the IGPL, 3, 167-190. >>>
  • Alechina, N. A., & van Lambalgen, M. (1996). Generalized quantification as substructural logic. Journal of Symbolic Logic, 61(3), 1006-1044. https://doi.org/10.2307/2275797 >>>
  • Alechina, N. A. (1995). Modal quantifiers. Institute for Logic, Language and Computation. >>>
  • Alechina, N. A. (1995). Logic with Probabilistic Operators. In Proceedings ACCOLADE'94 (pp. 121-138). >>>
  • Alechina, N. A. (1995). For All Typical. In Symbolic and Quantitative Approach to reasoning and Uncertainty. Proceedings ECSQARU'95 (pp. 1-8). Springer. >>>
  • Alechina, N. A. (1995). Logic with Probabilistic Operators. In Proceedings ACCOLADE'94 (pp. 121-138) >>>
  • Alechina, N. A. (1995). For All Typical. In Symbolic and Quantitative Approach to Reasoning and Uncertainty. Proceedings ECSQARU'95 (pp. 1-8). Springer. >>>
  • 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, 4(3), 177-189. >>>
  • Alexiadou, A., & Giannakidou, A. (1999). Specificational pseudoclefts as lists. In K. Shahin, S. Blake, & E-U. Kim (Eds.), Proceedings of the West Coast Conference on Formal Linguistics (WCCFL) XVII (pp. 1-16). CSLI Publications. >>>
  • Alhama, R. G., Scha, R., & Zuidema, W. (2014). Rule Learning in Humans and Animals. In E. A. Cartmill, S. Roberts, H. Lyn, & H. Cornish (Eds.), The Evolution of Language: proceedings of the 10th International Conference (EVOLANG10), Vienna, Austria, 14-17 April 2014 (pp. 371-372). World Scientific. https://doi.org/10.1142/9789814603638_0049 >>>
  • Alhama, R. G., Scha, R., & Zuidema, W. (2015). How should we evaluate models of segmentation in artificial language learning? In N. A. Taatgen, M. K. van Vugt, J. P. Borst, & K. Mehlhorn (Eds.), Proceedings of ICCM 2015: 13th International Conference on Cognitive Modeling : April 9-11, Groningen, The Netherlands (pp. 172-173). University of Groningen. http://www.cognitive-modeling.com/proceedings/ICCM2015_proceedings.pdf >>>
  • Alhama, R. G., & Zuidema, W. (2016). Pre-Wiring and Pre-Training: What does a neural network need to learn truly general identity rules? In T. R. Besold, A. Bordes, A. d'Avila Garcez, & G. Wayne (Eds.), CoCo 2016 : Cognitive Computation: 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 [4] (CEUR Workshop Proceedings; Vol. 1773). CEUR-WS. http://ceur-ws.org/Vol-1773/CoCoNIPS_2016_paper4.pdf >>>
  • Alhama, R. G., & Zuidema, W. (2016). Generalization in Artificial Language Learning: Modelling the Propensity to Generalize. In A. Korhonen, A. Lenci, B. Murphy, T. Poibeau, & A. Villavicencio (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. https://doi.org/10.18653/v1/W16-19 >>>
  • Alhama, R. G., & Zuidema, W. (2017). Segmentation as Retention and Recognition: the R&R model. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Eds.), CogSci 2017: proceedings of the 39th Annual Meeting of the Cognitive Science Society : London, UK : 26-29 July 2017 : Computational Foundations of Cognition (Vol. 2, pp. 1531-1536). Cognitive Science Society. https://cogsci.mindmodeling.org/2017/papers/0300/index.html >>>
  • Alhama, 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, 61, 927-946. https://doi.org/10.1613/jair.1.11197 >>>
  • Aliseda-Llera, A. (1997). Seeking Explanations: Abduction in Logic, Philosophy of Science and Artificial Intelligence. Universiteit van Amsterdam. >>>
  • Aliseda-Llera, A. (1997). Abduction as a model for belief revision. In Proceedings of the Taller de Logica y Computacion, Primer Encuentro de Computacion (pp. 1-7). Universidad de Queretaro. >>>
  • Aljanaki, A., Bountouridis, D., Burgoyne, J. A., Van Balen, J., Wiering, F., Honing, H., & Veltkamp, R. (2014). Designing Games with a Purpose for Data Collection in Music Research. Emotify and Hooked: Two Case Studies. In A. De Gloria (Ed.), Games and Learning Alliance: Second International Conference, GALA 2013, Paris, France, October 23-25, 2013 : revised selected papers (pp. 29-40). (Lecture Notes in Computer Science; Vol. 8605). Springer. https://doi.org/10.1007/978-3-319-12157-4_3 >>>

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