How to deal with a huge action space, where, at every step, there is a variable number of legal actions?
How can I incorporate domain knowledge to choose actions in the case of large action spaces in multi-armed bandits?
How to handle large dimensionality differences between state and action inputs in a reinforcement learning predictor?
Why does each component of the tuple that represents an action have a categorical distribution in the TRPO paper?
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