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#49 - Meta-Gradients in RL - Dr. Tom Zahavy (DeepMind)

Machine Learning Street Talk (MLST)

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Meta-Learning and Reinforcement Dynamics

This chapter investigates meta-learning, focusing on tuning hyperparameters for meta algorithms and exploring the implications in reinforcement learning (RL). It discusses the complexities of using meta gradients, the importance of diverse solutions, and the interplay between different optimization strategies. The dialogue also covers the role of planning horizons and discount factors in decision-making processes, emphasizing practical applications and challenges in RL systems.

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