Thoughts on RL with a changing action/state space
In the simplest implementations of reinforcement learning, state and action spaces are represented as tables. The entries in these tables correspond to the value estimates of particular states or actions. For these simple implementations, whether the action or state space are of a fixed size isn’t a concern. If a state has a different action […]
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