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cs.LG2021
Maximum Entropy Reinforcement Learning with Mixture Policies
Nir Baram, Guy Tennenholtz, Shie Mannor
Mixture models are an expressive hypothesis class that can approximate a rich set of policies. However, using mixture policies in the Maximum Entropy (MaxEnt) framework is not stra…
cs.LG2021
Action Redundancy in Reinforcement Learning
Nir Baram, Guy Tennenholtz, Shie Mannor
Maximum Entropy (MaxEnt) reinforcement learning is a powerful learning paradigm which seeks to maximize return under entropy regularization. However, action entropy does not necess…
cs.LG2018
Inspiration Learning through Preferences
Nir Baram, Shie Mannor
Current imitation learning techniques are too restrictive because they require the agent and expert to share the same action space. However, oftentimes agents that act differently…