Advances in Stochastic Control and Reinforcement Learning: Theory and Application (25w5428)


Yufei Zhang (Imperial College London)

Xin Guo (UC Berkeley)

Lukasz Szpruch (University of Edinburgh)

Renyuan Xu (University of Southern California)

Thaleia Zariphopoulou (The University of Texas at Austin)


The Banff International Research Station will host the “Advances in stochastic control and reinforcement learning: theory and application” workshop in Banff from April 27 - May 2, 2025.

A 5-day research workshop at the Banff International Research Station is set to unveil the mysteries surrounding reinforcement learning (RL) and its pivotal role in high-stakes decision-making. RL techniques, which power data-driven decision-making, are advancing rapidly. Yet, understanding their performance and quantifying inherent risks necessitate interdisciplinary collaboration. This event will bring together experts from fields like mathematics, statistics, computer science, economics, and engineering to explore cutting-edge developments in RL and its intersections with stochastic control, game, and human-machine interactive systems. By synthesizing knowledge and mathematical methodologies, the workshop aims to enhance the accuracy and reliability of decision-making across diverse domains, spanning energy and financial markets to healthcare. The event's diversity and focus on emerging areas will facilitate the creation of safer and more efficient RL algorithms for real-world applications.

The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Centre in Alberta and is supported by Canada’s Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), and Alberta’s Advanced Education and Technology.