Published
2026
Colizoli, O., van Leeuwen, T. M., Rutar, D., & Bekkering, H. (2026). Pupil dilation offers a time-window on prediction error. eLife, 14, RP105287.
Zhou, L., ... Rutar, D., ... & Hernández-Orallo, J. (2026). Predictable artificial intelligence. Artificial Intelligence, 104491.
2025
Rutar, D., Markelius, A., Schellaert, W., Hernández-Orallo, J., & Cheke, L. (2025). General interaction battery: Simple object navigation and affordances (GIBSONA). Cognitive Systems Research, 101411.
Rutar, D., de Wolff, E., & Kwisthout, J. (2025). The role of structural input properties in statistical learning. In Proceedings of The 46th Annual Meeting of the Cognitive Science Society. San Francisco. Longer version available here.
Ward, E. K., Rutar, D., Zaadnoordijk, L., Poli, F., & Hunnius, S. (2023). Beyond the adult mind: A developmental framework for predictive processing in infancy. Topics in Cognitive Science.
2023
Rutar, D., Colizoli, O., Selen, L., Spieß, L., Kwisthout, J., & Hunnius, S. (2023). Differentiating between Bayesian parameter learning and structure learning based on behavioural and pupil measures. PloS one, 18(2), e0270619.
Burnell, R.., ... Rutar, D., ... & Hernandez-Orallo, J. (2023). Rethink reporting of evaluation results in AI. Science, 380(6641), 136-138.
Rutar, D. (2023). Developing higher cognition through predictive processing. Journal of Contemporary Educational Studies/Sodobna Pedagogika, 74(3).
2022
Voudouris, K., Donnelly, N., Rutar, D., Burnell, R., Burden, J., Hernández-Orallo, J., & Cheke, L. G. (2022). Evaluating object permanence in embodied agents using the Animal-AI environment. In the CEUR Workshop Proceedings 2022.
Rutar, D., de Wolff, E., van Rooij, I., & Kwisthout, J. (2022). Structure learning in predictive processing needs revision. Computational Brain & Behavior, 5(2), 234-243.
Rutar, D., Wiese, W., & Kwisthout, J. (2022). From representations in predictive processing to degrees of representational features. Minds and Machines, 32(3), 461-484.
In preparation or under review/revision
Rutar, D., Markelius, A., Voudouris, K., Hernández-Orallo, J., & Cheke, L. Cognitive Science-Inspired Evaluation of Core Capabilities for Object Understanding in AI. Under review.
Rutar, D., Carcasi, F., Deane, G. The construction of concepts: Active inference and the probabilistic language of thought. Under review.
Burden, J., Burnell, R., Voudouris, K., Rutar, D., Cheke, L., & Hernández-Orallo. Inferring capabilities from task performance with Bayesian triangulation. Under review Journal of Machine Learning Research.