AI RESEARCH
On Distributional Reinforcement Learning in Chaotic Dynamical Systems
arXiv CS.AI
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ArXi:2605.30160v1 Announce Type: cross Chaotic dynamical systems pose a fundamental challenge for Reinforcement Learning (RL): exponential sensitivity to initial conditions induces high-variance bootstrap targets and poorly conditioned gradient updates. Chaotic dynamics arise across scientific and engineering domains, from fluid flows and climate systems to multi-agent systems, where reliable learning is highly desirable.