Foundations of RL and Control
Connections and New Perspectives
Workshop at the International Conference on Machine Learning (ICML) 2024 in Vienna, Austria
Despite rapid advances in machine learning, solving large-scale stochastic dynamic programming problems remains a significant challenge. The combination of neural networks with RL has opened new avenues for algorithm design, but the lack of theoretical guarantees of these approaches hinders their applicability to high-stake problems traditionally addressed using control theory, such as online supply chain optimization, industrial automation, and adaptive transportation systems. This workshop focuses on recent advances in developing a learning theory of decision (control) systems, that builds on techniques and concepts from two communities that have had limited interactions despite their shared target: reinforcement learning and control theory.
News
May 25, 2024 | The submission deadline has been extended to May 29, 2024 (AoE). |
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Confirmed Speakers
Organizers
Contact
If you have any questions, please contact us at forlac.workshop@gmail.com.