Joost Broekens
Associate professor
- Name
- Dr.ir. D.J. Broekens
- Telephone
- 071 5277139
- d.j.broekens@liacs.leidenuniv.nl
Joost Broekens studies Artificial Intelligence, in particular Affective Computing and the interaction between humans and socially interactive agents. He is the President Elect of the Association for the Advancement of Affective Computing (AAAC), which is the main international organisation in his research field. He is an associate professor and head of the Affective Computing and Human Robot Interaction group at the Leiden Institute of Advanced Computer Science (LIACS) of Leiden University. Besides this, Joost is a member of of the interdisciplinary research programme Society, Artificial Intelligence and Life Sciences (SAILS). Finally, he is also co-founder and CTO of Interactive Robotics, enabling students from any age to learn with and from social robots.
Joost Broekens studies Artificial Intelligence, in particular Affective Computing and the interaction between humans and socially interactive agents. He is the President Elect of the Association for the Advancement of Affective Computing (AAAC), which is the main international organisation in his research field. He is an associate professor and head of the Affective Computing and Human Robot Interaction group at the Leiden Institute of Advanced Computer Science (LIACS) of Leiden University. Besides this, he is a member of the interdisciplinary research programme Society, Artificial Intelligence and Life Sciences (SAILS). Finally, he is also co-founder and CTO of Interactive Robotics, enabling students from any age to learn with and from social robots.
His research interests include computational modelling of emotions in reinforcement learning, computational models of cognitive appraisal, emotion psychology, emotions in computer games, explainability of AI and transparency, human perception and effects of emotions expressed by virtual agents and robots, emotional and affective self-report, human-robot and human-agent interaction, and educational humanoid robots. His current research focuses on human-robot interaction, and Reinforcement Learning as a formal model for emotional appraisal.
Associate professor
- Faculty of Science
- Leiden Inst of Advanced Computer Science
- Rijgersberg-Peters R., Vught W. van, Broekens D.J. & Neerincx M.A. (2024), Goal ontology for personalized learning and its implementation in child's health self-management support, IEEE Transactions on Learning Technologies 17: 903-918.
- Zhang E.J., Hilpert B., Broekens D.J. & Jokinen P.P.J. (2024), Simulating emotions with an integrated computational model of appraisal and reinforcement learning. Floyd Mueller F., Kyburz P., Williamson J.R., Sas C., Wilson M.L., Toups Dugas P. & Shklovksi I. (Eds.), CHI '24: Proceedings of the 2024 CHI conference on human factors in computing systems. CHI EA '24: Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems 11 May 2024 - 16 May 2024. New York: Association for Computing Machinery. 703.
- Mast D., Broekens D.J., Vries S. de & Verbeek F.J. (2023), Participation patterns of interactive playful museum exhibits: evaluating the participant journey map through situated observations. Byrne D., Martelaro N., Boucher A., Chatting D., Fdili Alaoui S., Fox S., Nicenboim I. & MacArthur C. (Eds.), Proceedings of the ACM designing interactive systems conference. ACM Designing Interactive Systems Conference 10 July 2023 - 14 July 2023: Association for Computing Machinery. 1861-1885.
- Dudzik B., Hung H., Neerincx M. & Broekens D.J. (2023), Collecting mementos: a multimodal dataset for context-sensitive modeling of affect and memory processing in responses to videos, IEEE Transactions on Affective Computing 14(2): 1249-1266.
- Moerland T.M., Broekens D.J., Plaat A. & Jonker C.M. (2023), Model-based reinforcement learning: a survey, Foundations and Trends in Machine Learning 16(1): 1-118.
- Broekens D.J., Hilpert B., Verberne S., Baraka K., Gebhard P. & Plaat A. (2023), Fine-grained affective processing capabilities emerging from large language models, 2023 11th international conference on Affective Computing and Intelligent Interaction (ACII). 11th International Conference on Affective Computing and Intelligent Interaction (ACII) 10 September 2023 - 13 September 2023: IEEE. 1-8.
- Moerland T.M., Broekens D.J., Plaat A. & Jonker C.M. (2022), A unifying framework for reinforcement learning and planning, Frontiers in Artificial Intelligence 5: 908353.
- Mast D., Vries S.I. de, Broekens D.J. & Verbeek F.J. (2021), The participant journey map: understanding the design of interactive augmented play spaces, Frontiers in Computer Science 3: 674132.
- Moerland T.M., Deichler A., Baldi S., Broekens D.J. & Jonker C.M. (2020), Think too fast nor too slow: the computational trade-off between planning and reinforcement learning. Fern A., Gómez V., Jonsson A., Katz M., Palacios H. & Sanner S. (Eds.), Proceedings of the 1st workshop on bridging the gap between AI Planning and Reinforcement Learning (PRL). 30th International Conference on Automated Planning and Scheduling (ICAPS 19 October 2020 - 30 October 2020.
- Mast D., Vries S. de, Broekens D.J. & Verbeek F.J. (2020), The importance of the peak-end rule for repeated visits to Augmented Play Spaces. PERSUASIVE 2020 - 15th International conference on Persuasive Technology, Aalborg. 20 April 2020 - 23 April 2020. [conference poster].
- Moerland T.M., Broekens D.J. & Jonker C.M. (2018), Emotion in reinforcement learning agents and robots: a survey, Machine Learning 107: 443-480.
- Moerland T.M., Broekens D.J., Plaat A. & Jonker C.M. (2018), Monte Carlo tree search for asymmetric trees. Dy J. & Krause A. (Eds.), Proceedings of machine learning research. 35th International Conference on Machine Learning 10 July 2018 - 15 July 2018. Proceedings of Machine Learning Research no. 80: MLReseachPress.
- Moerland T.M., Broekens D.J., Plaat A. & Jonker C.M. (2018), A0C: Alpha zero in continuous action space. Dy J. & Krause A. (Eds.), Proceedings of machine learning research. 35th International Conference on Machine Learning 10 July 2018 - 15 July 2018. Proceedings of Machine Learning Research no. 80: MLReseachPress.
- Moerland T.M., Broekens D.J. & Jonker C.M. (2018), The potential of the return distribution for exploration in RL. ICML 2018 Workshop on Exploration in Reinforcement Learning 15 July 2018 - 15 July 2018.
- Moerland T.M., Broekens DJ. & Jonker C.M. (2017), Efficient exploration with Double Uncertain Value Networks. Deep Reinforcement Learning Symposium at the 30th Conference on Advances in Neural Information Processing Systems (NIPS). [conference paper].
- Moerland T.M., Broekens D.J. & Jonker C.M. (2017), Learning multimodal transition dynamics for model-based reinforcement learning. 1st Scaling-Up Reinforcement Learning (SURL) Workshop 18 September 2017 - 18 September 2017.
- Moerland T.M., Broekens D.J. & Jonker C.M. (2016), Fear and Hope Emerge from Anticipation in Model-Based Reinforcement Learning. Brewka G. (Ed.), IJCAI'16: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Twenty-Fifth International Joint Conference on Artificial Intelligence 9 July 2016 - 15 July 2016: AAAI Press. 848 - 854.
- Broekens D.J., Kosters W.A. & Verbeek F.J. (2007), On affect and self-adaptation: potential benefits of valence-controlled action-selection. Mira J. & Alvarez J.R. (Eds.), Bio-inspired modeling of cognitive tasks. International Work-Conference on the Interplay Between Natural and Artificial Computation IWINAC 2007: Bio-inspired Modeling of Cognitive Tasks 18 June 2007 - 21 June 2007. Lecture Notes in Computer Science no. 4527. Berlin/Heidelberg: Springer. 357-366.
- Broekens D.J. (18 December 2007), Affect and Learning: a computational analysis (Dissertatie. Leiden Institute of Advanced Computer Science (LIACS), Faculty of Science, Leiden University). Supervisor(s) and Co-supervisor(s): Kok J.N., Verbeek F.J & Kosters W.A.
- Broekens D.J., Kosters W.A. & Verbeek F.J. (2007), Affect, anticipation, and adaptation: affect-controlled selection of anticipatory simulation in artificial adaptive agents, Adaptive Behavior 15(4): 397-422.
- Broekens D.J. & Verbeek F.J. (2005), Simulation, emotion and information processing: computational investigations of the regulative role of pleasure in adaptive behavior modeling natural action selection, Proceedings of the workshop on modeling natural action selection. : AISB Press. 166-173.
- Wetenschappelijk adviseur
- Co-founder