AI RESEARCH
From Ticks to Flows: Dynamics of Neural Reinforcement Learning in Continuous Environments
arXiv CS.AI
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ArXi:2606.04275v1 Announce Type: cross We present a novel theoretical framework for deep reinforcement learning (RL) in continuous environments by modeling the problem as a continuous-time stochastic process, drawing on insights from stochastic control. Building on previous work, we