case class TickState[Obs, A, R, S[_]](state: State[Obs, A, R, S], tick: Int, limit: Int)(implicit evidence$1: Functor[S]) extends State[Obs, A, R, S] with Product with Serializable
State that ends after a certain number of interactions. This is useful for turning a non-episodic into an episodic task.
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- TickState.scala
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dynamics: Map[A, S[(R, This)]]
For every action you could take, returns a generator of the next set of rewards.
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Returns a list of possible actions to take from this state.
- val limit: Int
- def mapK[N[_]](f: FunctionK[S, N])(implicit N: Functor[N]): State[Obs, A, R, N]
- def mapObservation[P](f: (Obs) ⇒ P)(implicit S: Functor[S]): State[P, A, R, S]
- def mapReward[T](f: (R) ⇒ T)(implicit S: Functor[S]): State[Obs, A, T, S]
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ScalaRL
This is the API documentation for the ScalaRL functional reinforcement learning library.
Further documentation for ScalaRL can be found at the documentation site.
Check out the ScalaRL package list for all the goods.