Artificial Intelligence & Cognitive Engineering

University of Groningen > Faculty of Science and Engineering > Faculty Board FSE > FSE Research > Bernoulli Institute > Artificial Intelligence & Cognitive Engineering

  1. 2018
  2. Mohades Kasaei, H., Lopes, L. S., & Tomé, A. M. (2018). Coping with Context Change in Open-Ended Object Recognition without Explicit Context Information. Paper presented at 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, Madrid, Spain.
  3. Szymanik, J., & Verbrugge, R. (2018). Tractability and the computational mind. In M. Sprevak, & M. Colombo (Eds.), The Routledge Handbook of the Computational Mind (1st Editon ed., pp. 339-353). Oxford: Routledge.
  4. 2017
  5. Okafor, E., Pawara, P., Karaaba, M., Surinta, O., Codreanu, V., Schomaker, L., & Wiering, M. (2017). Comparative study between deep learning and bag of visual words for wild-animal recognition. In 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016 (2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016). Institute of Electrical and Electronics Engineers Inc..
  6. 2016
  7. 2015
  8. Renardel de Lavalette, G., Ghosh, S. (Ed.), & Szymanik, J. (Ed.) (2015). Infinitary hybrid logic and the Lindelöf property. In The Facts Matter. Essays on Logic and Cognition in Honour of Rineke Verbrugge: Tributes (Vol. 25, pp. 113-120). College Publications.
  9. 2014
  10. Kruitbosch, H. T., Giotis, I., & Biehl, M. (2014). Segmented Shape-Symbolic Time Series Representation. In M. Verleysen (Ed.), Proceedings of the 22. European Symposium on Artificial Neural Networks ESANN d-side publishing.
  11. 2013
  12. Ghosh, S., & de Jongh, D. (2013). Comparing strengths of beliefs explicitly. Logic Journal of the IGPL, 21(3), 488-514.
  13. Kooi, B., & van Ditmarsch, H. (2013). Honderd gevangenen en een gloeilamp. (Epsilon uitgaven). Utrecht: Epsilon Uitgaven.
  14. van der Ree, M., & Wiering, M. (2013). Reinforcement Learning in the Game of Othello: Learning Against a Fixed Opponent and Learning from Self-Play. In Proceedings of IEEE International Symposium on Adaptive Dynamic Programming and Reinforcement Learning: ADPRL
  15. 2012
  16. Mostowski, M., & Szymanik, J. (2012). Semantic bounds for everyday language. Semiotica, 2012(188), 323-332.
  17. Nijboer, M., Taatgen, N. A., & van Rijn, H. (2012). Choices, Choices: Task Selection Preference During Concurrent Multitasking. In N. Russwinkel, U. Drewitz, & H. Van Rijn (Eds.), Proceedings of the 11th international Conference on Cognitive Modeling (pp. 241-242). Berlin: Universitätsverlag der TU Berlin.
  18. Van Rijn, H., & Nijboer, M. (2012). Optimaal feiten leren met ICT. 4W: Weten Wat Werkt en Waarom, 1, 6 - 11.
  19. Szymanik, J., & Robaldo, L. (2012). Pragmatic Identification of the Witness Sets. In N. Calzolari (Ed.), Proceedings of the 8th Conference on Language resources and Evaluation Istanbul: European Language Resources Association (ELRA).
  20. 2011
  21. van Rooij, I., Kwisthout, J., Blokpoel, M., Szymanik, J., Wareham, T., & Toni, I. (2011). Intentional communication: Computationally easy or difficult? Frontiers in Human Neuroscience, 5, [52].
  22. Gierasimczuk, N., & Szymanik, J. (2011). A note on a generalization of the muddy children puzzle. In K. Apt (Ed.), Proceedings of the 13th Conference on Theoretical Aspects of Rationality and Knowledge (pp. 257-264). ACM Press Digital Library.
  23. Visser, T., Andringa, T., & Verbrugge, L. (2011). Affective agents bridge teh gap between life and mind. In T. Froese, M. Egbert, & X. Barandiaran (Eds.), Workshop on Artificial Autonomy ECAL 2011: Twenty Years of Practice of Autonomous Systems (pp. 7-12). Paris.
  24. Baltag, A., Gierasimczuk, N., & Smets, S. (2011). Belief revision as a truth tracking process. In K. Apt (Ed.), Proceedings of TARK (pp. 187-190). New York: ACM Press.
  25. Kontinen, J., & Szymanik, J. (2011). Characterizing definability of second-order generalized quantifiers. In L. D. Beklemishev, & R. de Quieroz (Eds.), Logic, Language, Information and Computation (Vol. 8652, pp. 187-200). (Lecture Notes on Computer Science; Vol. 8652). Berlin: Springer.
  26. Gierasimczuk, N., & Szymanik, J. (2011). Invariance properties of quantifiers and multiagent information exchange. In M. Kanazawa (Ed.), Proceedings of the 12th Meeting on Mathematics of Language (Vol. 6878, pp. 72-89). Berlin: Lecture Notes in Artificial Intelligence.
  27. Dégremont, C., Kurzen, L., & Szymanik, J. (2011). On the tractability of comparing informational structures. In J. van Eijck, & R. Verbrugge (Eds.), Proceedings of the Workshop on reasoning About Other Minds: Logical and Cognitive Perspectives (Vol. 751, pp. 50-64). CEUR Workshop Proceedings.
  28. Kooi, B., Ditmarsch, H. V., & Hoek, W. V. D. (2011). Reasoning about local properties in modal logic. In K. Tumer, P. Yolum, L. Sonenberg, & P. Stone (Eds.), Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (pp. 711-718). Richland: IFAAMAS.
  29. Bhowmik, T. K., van Oosten, J-P., & Schomaker, L. (2011). Segmental K-Means Learning with Mixture Distribution for HMM Based Handwriting Recognition. In SO. Kuznetsov, DP. Mandal, MK. Kundu, & SK. Pal (Eds.), PATTERN RECOGNITION AND MACHINE INTELLIGENCE (pp. 432-439). (Lecture Notes in Computer Science; Vol. 6744). BERLIN: Springer.
  30. Dégremont, C., Lowe, B., & Witzel, A. (2011). The synchronicity of dynamic epistemic logic. In K. R. Apt (Ed.), TARK XIII: Proceedings of the 13th Conference on Theoretical Aspects of Rationality and Knowledge (pp. 145-152). ACM Press Digital Library.
  31. 2010
  32. Borst, J. P., Taatgen, N. A., & Van Rijn, D. H. (2010). Locating the neural correlates of the problem state resource: Analyzing fMRI data on the basis of a computational model. In G. Gunzelmann, & D. D. Salvucci (Eds.), Proceedings of ICCM - 2010- Tenth International Conference on Cognitive Modeling (pp. 287-288). Philadelphia: PA.
  33. Taatgen, N. A., & Van Rijn, D. H. (2010). Nice graphs, Good R2, but still a poor fit? How to be more sure your model explains your data. In D. D. Salvucci, & G. Gunzelmann (Eds.), Proceedings of ICCM - 2010- Tenth International Conference on Cognitive Modeling (pp. 247-252). Philadelphia, PA.
  34. van Valkenhoef, G., van der Vaart, E. E., & Verbrugge, L. (2010). OOPS: An S5n prover for educational settings. In Proceedings of the 6th Workshop on Methods for Modalities (M4M-6): Revised version in Electronic Notes in Theoretical Computer Science (Vol. 162, pp. 249-261)
  35. Andringa, T. (2010). Smart, general, and situation specific sensors. In Smarter sensors, easier processing: 11th International Conference on the Simulation of Adaptive behavior (SAB2010) Paris.
  36. Andringa, T. (2010). Soundscape and Core Affect Regualtion. In Interspeech 2010 Lisbon.
  37. Andringa, T., & Krijnders, J. (2010). IPC No. WO/2010/107. Texture Based Signal Analysis and Recognition. (Patent No. PVT/NL2010/050144).
  38. Meijering, B., Van Maanen, L., Van Rijn, H., & Verbrugge, R. (2010). The facilitative effect of context on second-order social reasoning. In S. Ohlsson, & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 1423-1428). Austin, TX: Cognitive Science Society.
  39. 2009
  40. Slingerland, S., Mulder, M., van der Vaart, E. E., & Verbrugge, L. (2009). A multi-agent systems approach to gossip and the evolution of language. In N. A. Taatgen, & R. van Rijn (Eds.), Proceedings of the 31st Annual Meeting of the Cognitive Science Society (pp. 1609-1614). Austin: Cognitive Science Society.
  41. Verhoef, T., Lisetti, C., Barreto, A., Ortega, F., van der Zant, C., & Cnossen, F. (2009). Bio-sensing for Emotional Characterization without Word Labels. In J. A. Jacko (Ed.), Proceedings of the 13th International Conference on Human Computer Interaction (Vol. 5612, pp. 693-702). (Lecture Notes in Computer Science). Springer.
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