com.cra.figaro.algorithm.decision

DecisionImportance

abstract class DecisionImportance[T, U] extends WeightedSampler with DecisionAlgorithm[T, U]

Importance sampling for decisions. Almost the exact same as normal importance sampling except that it keeps track of utilities and probabilities (to compute expected utility) and it implements DecisionAlgorithm trait

Linear Supertypes
DecisionAlgorithm[T, U], WeightedSampler, Sampler, ProbQueryAlgorithm, Algorithm, AnyRef, Any
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Inherited
  1. DecisionImportance
  2. DecisionAlgorithm
  3. WeightedSampler
  4. Sampler
  5. ProbQueryAlgorithm
  6. Algorithm
  7. AnyRef
  8. Any
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  1. Public
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Instance Constructors

  1. new DecisionImportance(universe: Universe, utilityNodes: List[Element[_]], decisionTarget: Decision[T, U])

Type Members

  1. type Sample = (Double, Map[Element[_], Any])

    A sample consists of a weight and a map from elements to their values.

    A sample consists of a weight and a map from elements to their values.

    Definition Classes
    WeightedSampler

  2. type WeightSeen[T] = (Element[T], Map[T, Double])

    Attributes
    protected
    Definition Classes
    WeightedSampler

Abstract Value Members

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

    Attributes
    protected
    Definition Classes
    ProbQueryAlgorithm

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

    Attributes
    protected
    Definition Classes
    ProbQueryAlgorithm

  3. abstract def doKill(): Unit

    Attributes
    protected
    Definition Classes
    Algorithm

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

    Attributes
    protected
    Definition Classes
    ProbQueryAlgorithm

  5. abstract def doResume(): Unit

    Attributes
    protected
    Definition Classes
    Algorithm

  6. abstract def doStart(): Unit

    Attributes
    protected
    Definition Classes
    Algorithm

  7. abstract def doStop(): Unit

    Attributes
    protected
    Definition Classes
    Algorithm

Concrete Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any

  6. var active: Boolean

    Attributes
    protected
    Definition Classes
    Algorithm

  7. var allWeightsSeen: List[WeightSeen[_]]

    Attributes
    protected
    Definition Classes
    WeightedSampler

  8. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  9. 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

  10. def cleanup(): Unit

    Cleans up the temporary elements created during sampling

  11. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    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
    WeightedSampler → ProbQueryAlgorithm

  13. 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
    WeightedSampler → ProbQueryAlgorithm

  14. 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

  15. 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
    DecisionImportance → DecisionAlgorithm

  16. 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

  17. def doSample(): Unit

    Attributes
    protected
    Definition Classes
    DecisionImportance → WeightedSampler → Sampler

  18. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  19. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  20. 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

  21. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  22. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

  23. def getTotalWeight: Double

    Total weight of samples taken.

    Total weight of samples taken.

    Definition Classes
    WeightedSampler

  24. 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

  25. 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

  26. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  27. 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

  28. def isActive: Boolean

    Definition Classes
    Algorithm

  29. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  30. 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

  31. 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

  32. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  33. def newWeightSeen[T](target: Element[T]): (Element[T], Map[T, Double])

    Attributes
    protected
    Definition Classes
    WeightedSampler

  34. final def notify(): Unit

    Definition Classes
    AnyRef

  35. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  36. 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

  37. 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

  38. 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

  39. lazy val queryTargets: List[Element[_]]

    Definition Classes
    WeightedSampler → ProbQueryAlgorithm

  40. def resetCounts(): Unit

    Attributes
    protected
    Definition Classes
    DecisionImportance → WeightedSampler → Sampler

  41. 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

  42. final def sample(): (Double, Map[Element[_], Any])

    Produce one weighted sample of the given element.

    Produce one weighted sample of the given element. weightedSample takes into account conditions and constraints on all elements in the Universe, including those that depend on this element.

    For decisions, our weight is actually the weight of the sampled state times the sum of the utility nodes. This will be used as the "weight" in the weighted sampler, ie, we are accumulating the expected utility of each state. Note that the weights will not be normalized, but that is ok since strategies are an optimization and everything will be divided by a constant

    Definition Classes
    DecisionImportance → WeightedSampler
    Annotations
    @tailrec()

  43. 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

  44. 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

  45. 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

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

    Definition Classes
    AnyRef

  47. def toString(): String

    Definition Classes
    AnyRef → Any

  48. var totalWeight: Double

    Attributes
    protected
    Definition Classes
    WeightedSampler

  49. val universe: Universe

    Definition Classes
    DecisionImportance → WeightedSampler → ProbQueryAlgorithm

  50. def update(): Unit

    Attributes
    protected
    Definition Classes
    WeightedSampler → Sampler

  51. def updateWeightSeenForTarget[T](sample: (Double, Map[Element[_], Any]), weightSeen: (Element[T], Map[T, Double])): Unit

    Attributes
    protected
    Definition Classes
    WeightedSampler

  52. def updateWeightSeenForTargetNoLog[T](sample: (Double, Map[Element[_], Any]), weightSeen: (Element[T], Map[T, Double])): Unit

    Attributes
    protected

  53. def updateWeightSeenWithValue[T](value: T, weight: Double, weightSeen: (Element[T], Map[T, Double])): Unit

    Attributes
    protected
    Definition Classes
    WeightedSampler

  54. def updateWeightSeenWithValueNoLog[T](value: T, weight: Double, weightSeen: (Element[T], Map[T, Double])): Unit

    Attributes
    protected

  55. 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

  56. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  58. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from DecisionAlgorithm[T, U]

Inherited from WeightedSampler

Inherited from Sampler

Inherited from ProbQueryAlgorithm

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

Ungrouped