I am fascinated by the question of how humans and other animals learn adaptive goal-directed behavior from their interactions with the world. My research goal is to help the development of autonomous embodied agents with a similar skillset. To work towards this goal, I follow two research directions:

1. AI research: I research how to improve decision-making in deep learning agents. More specifically, I work towards agents that explore interesting behavior, plan far into the future, and can reuse their knowledge in new situations. This includes research on generalization, temporal abstraction, world models, and intrinsic motivation.

2. Cognitive modeling: I use the same methods to build computational cognitive models. Here I hope to shine light into the mechanisms and representations that give rise to the adaptive behavior of humans. This includes modeling event segmentation, epistemic gaze behavior, and multimodal speech processing.

Full list of publications on Google scholar: https://scholar.google.de/citations?user=FQOFw5cAAAAJ&hl=de

• C. Gumbsch, N. Sajid, G. Martius, & M.V. Butz (2024), Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics. In International Conference on Learning Representations (ICLR 2024), https: //openreview.net/pdf?id=5qappsbO73r, (spotlight, 5%)
• C. Gumbsch, M. Adam, B. Elsner, G. Martius, & M.V. Butz (2022), Developing hierarchical anticipations via neural network-based event segmentation. In 2022 IEEE International Conference on Development and Learning (ICDL 2022), https: //arxiv.org/pdf/2206.02042.pdf
• M. Eppe, C. Gumbsch, M. Kerzel, P.D. Nguyen, M.V. Butz,  & S. Wermter (2022), Intelligent problem-solving as integrated hierarchical reinforcement learning. Nature Machine Intelligence, 4 (2022), 11-20, https://rdcu.be/cFGsE
• C. Gumbsch, M.V. Butz, & G. Martius (2021), Sparsely changing latent states for prediction and planning in partially observable domains. In Advances in Neural Information Processing Systems (NeurIPS 2021), 34, 17518-17531, https:// openreview.net/pdf?id=-VjKyYX-PI9
• C. Gumbsch, M. Adam, B. Elsner, & M.V. Butz (2021), Emergent Goal-Anticipatory Gaze in Infants via Event-Predictive Learning and Inference. Cognitive Science, 45, e13016. https://doi.org/10.1111/cogs.13016
• C. Gumbsch, M. V. Butz, & G. Martius (2019), Autonomous identification and goal-directed invocation of event-predictive behavioral primitives, IEEE Transactions on Cognitive and Developmental Systems (2019). https://doi.org/10.1109/TCDS. 2019.2925890