Papers

Concept learning, prediction, and structured thought 

• Rutar, D., Carcasi, F., Deane, G. The construction of concepts: Active inference and the probabilistic language of thought. Under review. 

• Colizoli, O., van Leeuwen, T. M., Rutar, D., & Bekkering, H. (2026). Pupil dilation offers a time-window on prediction error. eLife, 14, RP105287. 

• 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. 

• Rutar, D. (2023). Developing higher cognition through predictive processing. Journal of Contemporary Educational Studies/Sodobna Pedagogika, 74(3). 

• 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. 

• 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. 

• 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. 

Cognitively inspired evaluation of artificial intelligence 

• Burden, J., Burnell, R., Voudouris, K., Rutar, D., Cheke, L., & Hernández-Orallo. Inferring capabilities from task performance with Bayesian triangulation. Under review.

• 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. 

• Zhou, L., ... Rutar, D., ... & Hernández-Orallo, J. (2026). Predictable artificial intelligence. Artificial Intelligence, 104491. 

• 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. 

• Burnell, R.., ... Rutar, D., ... & Hernandez-Orallo, J. (2023). Rethink reporting of evaluation results in AI. Science, 380(6641), 136-138. 

• 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.