Publications

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Z
Zuidema, W. (2002). Language adaptation helps language acquisition. In From Animals to Animats: Proceedings of the 7th Conference on the Simulation of Adaptive Behavior.
Zuidema, W., & Hogeweg, P.. (2000). Selective advantages of syntactic language: a model study. In Gleitman & Joshi, Proceedings of the 22nd Annual Meeting of the Cognitive Science Society (pp. 577-582). Mahwah, New Jersey: Lawrence Erlbaum Associates.
Zuidema, W., & Hogeweg, P.. (2000). Social patterns guide evolving grammars. In Evolution of Language 2000.
Zuidema, W. (2001). Emergent syntax: the unremitting value of computational modeling for understanding the origins of complex language. In J. Kelemen & Sos\'ık, P., Advances in Artificial Life (Proceedings 6th European Conference on Artificial Life, Prague) (Vol. 2159, pp. 641-644). Berlin: Springer.
Y
Yahyaa, S. Q., & Bernard, M.. (2014). Online Knowledge Gradient Exploration in an Unknown Environment. The 6th International Conference on Agents and Artificial Intelligence (ICAART). LERIA, University of Angers, France.
Yahyaa, S. Q., Drugan, M. M., & Manderick, B.. (2014). Knowledge Gradient for Multi-objective Multi-armed Bandit Algorithms. In ICAART 2014 : International Conference on Agents and Artificial Intelligence.. presented at the 03/2014.
MOMAB-KG.pdf (201.8 KB)
Annealing_Normal_WorkShop.pdf (235.29 KB)
Yahyaa, S. Q., Drugan, M. M., & Manderick, B.. (2014). Linear Scalarized Knowledge Gradient in the Multi-Objective Multi-Armed Bandits Problem. In European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2014). presented at the 04/2014.
VER3-LSKGinMOMAB-esann.pdf (259.84 KB)
Yahyaa, S. Q., Drugan, M. M., & Bernard, M.. (2014). Knowledge Gradient for Multi-objective Multi-armed Bandit Algorithms. In The French Meeting on Planning, Decision Making and Learning (JFPDA). presented at the 2014.
MOMAB-KG-Leige.pdf (508.28 KB)
Yahyaa, S. Q., Drugan, M. M., & Bernard, M.. (2014). Exploration vs Exploitation in the Multi-Objective Multi-Armed Bandit Problem. In International Joint Conference on Neural Networks (IJCNN). presented at the 07/2014, Beijng: IEEE.
Yahyaa, S. Q., & Bernard, M.. (2013). Empirical Evaluation of Shortest Path Gaussian Kernels over State Action Graphs. The 5th International Conference on Agents and Artificial Intelligence (ICAART). Barcelona, Spain.
Yahyaa, S. Q., & Bernard, M.. (2013). “Knowledge Gradient Exploration in Online Kernal-Based LSPI. In The 25th Benelux Conference on Artificial Intelligence (BNAIC). Delft, The Netherlands.
Yahyaa, S. Q., & Bernard, M.. (2012). Shortest Path Gaussian Kernels for State Action Graphs: An Empirical Study. In The 24th Benelux Conference on Artificial Intelligence (BNAIC). Maastricht, The Netherlands.
Yahyaa, S. Q., & Bernard, M.. (2012). The Exploration vs Exploitation Trade-Off in the Multi-Armed Bandit Problem: An Empirical Study. Proceedings of the 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN). presented at the 04/2012, Bruges, Belgium.
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WilsonandLittle Protolang abstract.pdf (84.31 KB)
Werner, B., Dingli, D., Lenaerts, T., Pacheco, J. M., & Traulsen, A.. (2011). Dynamics of Mutant Cells in Hierarchical Organized Tissues. PLoS Comput Biol, 7, e1002290. presented at the 12. doi:10.1371/journal.pcbi.1002290
Wellens, P. (2008). Coping with Combinatorial Uncertainty in Word Learning: A Flexible Usage-Based Model. In A. D. M. Smith, Smith, K., & Ferrer-i-Cancho, R., The Evolution of Language. Proceedings of the 7th International Conference (EVOLANG 7) (pp. 370–377). Singapore: World Scientific Press.
evolang7.pdf (414.27 KB)
Wellens, P., van Trijp, R., Steels, L., & Beuls, K.. (2013). Fluid Construction Grammar for Historical and Evolutionary Linguistics. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics. presented at the 08/2013, Sofia, Bulgary.
P13-4022.pdf (1.3 MB)
Wellens, P., van Trijp, R., Beuls, K., & Steels, L.. (2013). Fluid Construction Grammar for Historical and Evolutionary Linguistics. In Proceedings of 51st Annual Meeting of the Association for Computational Linguistics. presented at the August, Sofia, Bulgaria: Association for Computational Linguistics.
Wellens-evolang8.pdf (231.74 KB)

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