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Methodology2-WPS Office by cobi2952 is a document available to read on EtoBox.

This study employs a systematic, simulation-driven research approach to investigate the limitations of deep reinforcement learning (RL) agents in adapting to dynamic environments, addressing the Simulation-to-Reality (Sim2Real) gap. The methodology is structured around three pillars: enhancing the agent, adapting the environment, and ensuring rigorous evaluation and transparency, with a focus on the CartPole control task as a testbed for generalization research. The evaluation strategy includes zero-shot ge

Author
cobi2952
Language
EN