OneTimeProbQueryDecision

Abstract Value Members

abstract def computeDistribution[T](target: Element[T]): Stream[(Double, T)]

Return an estimate of the marginal probability distribution over the target that lists each element with its probability.
Return an estimate of the marginal probability distribution over the target that lists each element with its probability. The result is a lazy stream. It is up to the algorithm how the stream is ordered.

Definition Classes
ProbQueryAlgorithm
abstract def computeExpectation[T](target: Element[T], function: (T) ⇒ Double): Double

Return an estimate of the expectation of the function under the marginal probability distribution of the target.
Return an estimate of the expectation of the function under the marginal probability distribution of the target.

Definition Classes
ProbQueryAlgorithm
abstract def computeUtility(): Map[(T, U), DecisionSample]

Compute the utility of each parent/decision tuple and return a DecisionSample.
Compute the utility of each parent/decision tuple and return a DecisionSample. Each decision algorithm must define how this is done since it is used to set the policy for a decision. For sampling algorithms, this will me a map of parent/decision tuples to a utility and a weight for that combination. For factored algorithms, the DecisionSample will contain the exact expected utility with a weight of 1.0.

Definition Classes
DecisionAlgorithm
abstract val queryTargets: Seq[Element[_]]

Definition Classes
ProbQueryAlgorithm
abstract def run(): Unit

Run the algorithm, performing its computation to completion.
Run the algorithm, performing its computation to completion.

Definition Classes
OneTime
abstract val universe: Universe

Definition Classes
ProbQueryAlgorithm

Concrete Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
var active: Boolean

Attributes
protected
Definition Classes
Algorithm
final def asInstanceOf[T0]: T0

Definition Classes
Any
def cleanUp(): Unit

Called when the algorithm is killed.
Called when the algorithm is killed. By default, does nothing. Can be overridden.

Definition Classes
Algorithm
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def computeProbability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double

Return an estimate of the probability of the predicate under the marginal probability distribution of the target.
Return an estimate of the probability of the predicate under the marginal probability distribution of the target.

Definition Classes
ProbQueryAlgorithm
def distribution[T](target: Element[T]): Stream[(Double, T)]

Return an estimate of the marginal probability distribution over the target that lists each element with its probability.
Return an estimate of the marginal probability distribution over the target that lists each element with its probability. The result is a lazy stream. It is up to the algorithm how the stream is ordered. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

Definition Classes
ProbQueryAlgorithm
def doDistribution[T](target: Element[T]): Stream[(Double, T)]

Attributes
protected
Definition Classes
OneTimeProbQuery → ProbQueryAlgorithm
def doExpectation[T](target: Element[T], function: (T) ⇒ Double): Double

Attributes
protected
Definition Classes
OneTimeProbQuery → ProbQueryAlgorithm
def doKill(): Unit

Attributes
protected
Definition Classes
OneTime → Algorithm
def doProbability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double

Attributes
protected
Definition Classes
OneTimeProbQuery → ProbQueryAlgorithm
def doResume(): Unit

Attributes
protected
Definition Classes
OneTime → Algorithm
def doStart(): Unit

Attributes
protected
Definition Classes
OneTime → Algorithm
def doStop(): Unit

Attributes
protected
Definition Classes
OneTime → Algorithm
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def expectation[T](target: Element[T], function: (T) ⇒ Double): Double

Return an estimate of the expectation of the function under the marginal probability distribution of the target.
Return an estimate of the expectation of the function under the marginal probability distribution of the target. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

Definition Classes
ProbQueryAlgorithm
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def getUtility(p: T, d: U): DecisionSample

Get the total utility and weight for a specific value of a parent and decision.
Get the total utility and weight for a specific value of a parent and decision.

Definition Classes
DecisionAlgorithm
def getUtility(): Map[(T, U), DecisionSample]

Get the total utility and weight for all sampled values of the parent and decision.
Get the total utility and weight for all sampled values of the parent and decision.

Definition Classes
DecisionAlgorithm
def hashCode(): Int

Definition Classes
AnyRef → Any
def initialize(): Unit

Called when the algorithm is started before running any steps.
Called when the algorithm is started before running any steps. By default, does nothing. Can be overridden.

Definition Classes
Algorithm
def isActive: Boolean

Definition Classes
Algorithm
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
def kill(): Unit

Kill the algorithm so that it is inactive.
Kill the algorithm so that it is inactive. It will no longer be able to provide answers.Throws AlgorithmInactiveException if the algorithm is not active.

Definition Classes
Algorithm
def mean(target: Element[Double]): Double

Return the mean of the probability density function for the given continuous element.
Return the mean of the probability density function for the given continuous element.

Definition Classes
ProbQueryAlgorithm
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def posteriorElement[T](target: Element[T], universe: Universe = Universe.universe): Element[T]

Return an element representing the posterior probability distribution of the given element.
Return an element representing the posterior probability distribution of the given element.

Definition Classes
ProbQueryAlgorithm
def probability[T](target: Element[T], value: T): Double

Return an estimate of the probability that the target produces the value.
Return an estimate of the probability that the target produces the value. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

Definition Classes
ProbQueryAlgorithm
def probability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double

Return an estimate of the probability of the predicate under the marginal probability distribution of the target.
Return an estimate of the probability of the predicate under the marginal probability distribution of the target. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

Definition Classes
ProbQueryAlgorithm
def resume(): Unit

Resume the computation of the algorithm, if it has been stopped.
Resume the computation of the algorithm, if it has been stopped. Throws AlgorithmInactiveException if the algorithm is not active.

Definition Classes
Algorithm
def setPolicy(e: Decision[T, U]): Unit

Sets the policy for the given decision.
Sets the policy for the given decision. This will get the computed utility of the algorithm and call setPolicy on the decision. Note there is no error checking here, so the decision in the argument must match the target decision in the algorithm.

Definition Classes
DecisionAlgorithm
def start(): Unit

Start the algorithm and make it active.
Start the algorithm and make it active. After it returns, the algorithm must be ready to provide answers. Throws AlgorithmActiveException if the algorithm is already active.

Definition Classes
Algorithm
def stop(): Unit

Stop the algorithm from computing.
Stop the algorithm from computing. The algorithm is still ready to provide answers after it returns. Throws AlgorithmInactiveException if the algorithm is not active.

Definition Classes
Algorithm
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
def variance(target: Element[Double]): Double

Return the variance of the probability density function for the given continuous element.
Return the variance of the probability density function for the given continuous element.

Definition Classes
ProbQueryAlgorithm
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

trait OneTimeProbQueryDecision[T, U] extends OneTimeProbQuery with DecisionAlgorithm[T, U]

Abstract Value Members

abstract def computeDistribution[T](target: Element[T]): Stream[(Double, T)]

abstract def computeExpectation[T](target: Element[T], function: (T) ⇒ Double): Double

abstract def computeUtility(): Map[(T, U), DecisionSample]

abstract val queryTargets: Seq[Element[_]]

abstract def run(): Unit

abstract val universe: Universe

Concrete Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

var active: Boolean

final def asInstanceOf[T0]: T0

def cleanUp(): Unit

def clone(): AnyRef

def computeProbability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double

def distribution[T](target: Element[T]): Stream[(Double, T)]

def doDistribution[T](target: Element[T]): Stream[(Double, T)]

def doExpectation[T](target: Element[T], function: (T) ⇒ Double): Double

def doKill(): Unit

def doProbability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double

def doResume(): Unit

def doStart(): Unit

def doStop(): Unit

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def expectation[T](target: Element[T], function: (T) ⇒ Double): Double

def finalize(): Unit

final def getClass(): Class[_]

def getUtility(p: T, d: U): DecisionSample

def getUtility(): Map[(T, U), DecisionSample]

def hashCode(): Int

def initialize(): Unit

def isActive: Boolean

final def isInstanceOf[T0]: Boolean

def kill(): Unit

def mean(target: Element[Double]): Double

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def posteriorElement[T](target: Element[T], universe: Universe = Universe.universe): Element[T]

def probability[T](target: Element[T], value: T): Double

def probability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double

def resume(): Unit

def setPolicy(e: Decision[T, U]): Unit

def start(): Unit

def stop(): Unit

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

def variance(target: Element[Double]): Double

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

Inherited from DecisionAlgorithm[T, U]

Inherited from OneTimeProbQuery

Inherited from OneTime

Inherited from ProbQueryAlgorithm

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

Ungrouped