trait StateValueFn[Obs, T] extends AnyRef
Along with ActionValueFn, this is the main trait in tabular reinforcement learning for tracking the value of a state as evidenced by the observation it returns.
We need some way for this to learn, or see new observations, that's part of the trait.
- Obs
Observation returned by the State instances tracked by StateValueFn.
- T
type of values tracked by StateValueFn.
- Self Type
- StateValueFn[Obs, T]
- Source
- StateValueFn.scala
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Abstract Value Members
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abstract
def
seen: Iterable[Obs]
Returns an Iterable of all observations associated with some internally tracked value T.
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abstract
def
stateValue(obs: Obs): T
Returns the stored value associated with the given observation.
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abstract
def
update(state: Obs, value: T): StateValueFn[Obs, T]
Absorb a new value for the supplied observation.
Absorb a new value for the supplied observation. The behavior of this function is implementation dependent; some might ignore the value, some might merge it in to an existing set of values, some might completely replace the stored state.
Concrete Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
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def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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clone(): AnyRef
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def
eq(arg0: AnyRef): Boolean
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equals(arg0: Any): Boolean
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def
finalize(): Unit
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def
fold[U](prepare: (U) ⇒ T, present: (T) ⇒ U): StateValueFn[Obs, U]
Transforms this StateValueFn into a new instance that applies the supplied
prepare
to all incoming values before they're learned, and presents tracked T instances using thepresent
fn before returning them via stateValue. -
final
def
getClass(): Class[_]
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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def
mergeable(implicit T: Semigroup[T]): StateValueFn[Obs, T]
Returns a StateValueFn instance that uses the supplied semigroup T to merge values into this current StateValueFn.
Returns a StateValueFn instance that uses the supplied semigroup T to merge values into this current StateValueFn.
- T
Semigroup instance used to merge values.
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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def
notifyAll(): Unit
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def
synchronized[T0](arg0: ⇒ T0): T0
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def
toEvaluator[A, R, S[_]]: StateValue[Obs, A, R, T, S]
TODO fill in.
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def
toString(): String
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def
wait(): Unit
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wait(arg0: Long, arg1: Int): Unit
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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.