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Malte Schwarzkopf

2 accepted papers

2025

Online Reinforcement Learning in Non-Stationary Context-Driven Environments

ICLR 2025spotlight

We study online reinforcement learning (RL) in non-stationary environments, where a time-varying exogenous context process affects the environment dynamics. Online RL is challenging in such environments due to "catastrophic forgetting" (CF). The agent tends to forget prior knowledge as it trains on…

2019

Variance Reduction for Reinforcement Learning in Input-Driven Environments

ICLR 2019poster

We consider reinforcement learning in input-driven environments, where an exogenous, stochastic input process affects the dynamics of the system. Input processes arise in many applications, including queuing systems, robotics control with disturbances, and object tracking. Since the state dynamics a…

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