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Workshop on Modern Applications of Control Theory and Reinforcement Learning, 20-21 May 2025, at CWI, Amsterdam, Netherlands

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Aditya Gilra

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May 11, 2025, 5:42:07 AMMay 11
to Systems Neuroscience
Dear all,
 
Final reminder for this exciting Workshop on Modern Applications of Control Theory and Reinforcement Learning:
 
Control theory and reinforcement learning (RL) converge on a shared objective: facilitating autonomous, real-time decision-making to optimise dynamical processes. Methods from control and RL are being increasingly applied to diverse fields, in particular complex adaptive systems such as climate-socio-economics, neuroscience, and similar. Finding safe, robust and optimal interventions on these systems will be crucial for the benefit of society. This workshop aims to foster the transfer of methods of control and RL across these upcoming domains. The workshop is open to all, especially (budding) researchers who would like to apply these methods to real-world complex systems.
Dates: 20-21 May 2025
Venue: CWI (Research Institute for Mathematics and Computer Science), Amsterdam, Netherlands
We welcome poster presentations from attendees.
 
Distinguished researchers will discuss methods used in a variety of domains, from critical network infrastructure like power grids, to sustainability economics and neuroscience:
Diederik Roijers, VU Brussel, Belgium - A Plea for User-Centred RL
Elena Rovenskaya, International Institute for Applied Systems Analysis (IIASA), Austria - Optimal Control and the Stories We Tell About Climate Change Economics
Herke van Hoof, University of Amsterdam, Netherlands - Reinforcement learning for real-world network infrastructure
Marcel van Gerven, Radboud University Nijmegen, Netherlands - Harnessing Noise for Neuromorphic Control
Marta Kwiatkowska, University of Oxford, United Kingdom - Provable guarantees for data-driven policy synthesis: a formal verification perspective
Sander Bohté, CWI, University of Amsterdam, Netherlands - Scaling Biologically Plausible Deep Reinforcement Learning
Sander Keemink, Radboud University Nijmegen, Netherlands - To spike or not to spike: using brain-like signals for control
Timm Faulwasser, Hamburg University of Technology, Germany - TBA
Wolfram Barfuss, University of Bonn, Germany - Collective Reinforcement Learning Dynamics for Sustainability Economics
 
Banner Workhop on Modern Applications of Control Theory and Reinforcement Learning
 
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