Trends in Reinforcement Learning with Pablo Samuel Castro - #443
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Reinforcement Learning: The Power of Small Environments
This chapter explores the importance of small and mid-scale environments in reinforcement learning research, showcasing their role in experimentation and discovery. It highlights unexpected findings, such as the preference for mean squared error over Huber loss, and emphasizes the need for inclusivity in research approaches. The discussion also addresses the challenges of large-scale benchmarks and the intricacies of language models compared to RL, pushing for broader evaluations of algorithm performance.
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