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trait State[A, Reward] extends AnyRef

A world should probably have a generator of states and actions... and then you can use that to get to the next thing. The state here is going to be useful in the Markov model; for the bandit we only have a single state, not that useful.

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State.scala
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  1. abstract def dynamics: Map[A, Generator[(Reward, State[A, Reward])]]

    For every action you could take, returns a generator of the next set of rewards.

    For every action you could take, returns a generator of the next set of rewards. This is a real world, or a sample model. If we want the full distribution we're going to have to build out a better interface. Good enough for now.

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  4. def act(action: A): Option[Generator[(Reward, State[A, Reward])]]

    Return None if it's an invalid action, otherwise gives us the next state.

    Return None if it's an invalid action, otherwise gives us the next state. (Make this better later.)

  5. def actions: Set[A]

    Returns a list of possible actions to take from this state.

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