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Training generalist agents is difficult across several axes, requiring us to deal with high-dimensional inputs (space), long horizons (time), and generalization to novel tasks.
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Language conditioned imitation learning over unstructured data
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Safe model-based reinforcement learning with stability guarantees
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Brent Harrison, Upol Ehsan, and Mark O Riedl · 2017
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Grounded language learning in a simulated 3D world
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A survey of inverse reinforcement learning: Challenges, methods and progress, 2018
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Lipschitz continuity in model-based reinforcement learning
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