6min chapter

Machine Learning Street Talk (MLST) cover image

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

Machine Learning Street Talk (MLST)

CHAPTER

Exploring Hierarchical State Spaces in DQN Agent

This chapter explores a research paper from 2011 that investigates the structure learned by a DQN agent trained on the game Breakout. The researchers use a Tizny projection to uncover hierarchical state spaces and develop an algorithm called abstract MDP, but encounter challenges in effectively utilizing the discovered structure.

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