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# BeliefPropagation 

### Companion trait BeliefPropagation

#### object BeliefPropagation

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### Value Members

1. final def !=(arg0: Any): Boolean
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2. final def ##(): Int
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3. final def ==(arg0: Any): Boolean
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4. def apply(dependentUniverses: List[(Universe, List[NamedEvidence[_]])], dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double, targets: Element[_]*)(implicit universe: Universe)

Create a Anytime belief propagation computer using the given dependent universes in the current default universe.

Create a Anytime belief propagation computer using the given dependent universes in the current default universe. Use the given dependent algorithm function to determine the algorithm to use to compute probability of evidence in each dependent universe.

5. def apply(dependentUniverses: List[(Universe, List[NamedEvidence[_]])], dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double, myIterations: Int, targets: Element[_]*)(implicit universe: Universe): ProbQueryBeliefPropagation with OneTimeProbabilisticBeliefPropagation with OneTimeProbQuery { val iterations: Int }

Create a One Time belief propagation computer using the given dependent universes in the current default universe.

Create a One Time belief propagation computer using the given dependent universes in the current default universe. Use the given dependent algorithm function to determine the algorithm to use to compute probability of evidence in each dependent universe.

6. def apply(dependentUniverses: List[(Universe, List[NamedEvidence[_]])], targets: Element[_]*)(implicit universe: Universe)

Create a One Time belief propagation computer using the given dependent universes in the current default universe.

7. def apply(dependentUniverses: List[(Universe, List[NamedEvidence[_]])], myIterations: Int, targets: Element[_]*)(implicit universe: Universe): ProbQueryBeliefPropagation with OneTimeProbabilisticBeliefPropagation with OneTimeProbQuery { val iterations: Int }

Create a Anytime belief propagation computer using the given dependent universes in the current default universe.

8. def apply(targets: Element[_]*)(implicit universe: Universe)

Creates a Anytime belief propagation computer in the current default universe.

9. def apply(myIterations: Int, targets: Element[_]*)(implicit universe: Universe): ProbQueryBeliefPropagation with OneTimeProbabilisticBeliefPropagation with OneTimeProbQuery { val iterations: Int }

Creates a One Time belief propagation computer in the current default universe.

10. final def asInstanceOf[T0]: T0
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11. def clone(): AnyRef
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12. def debugged(myIterations: Int, targets: Element[_]*)(implicit universe: Universe): ProbQueryBeliefPropagation with OneTimeProbabilisticBeliefPropagation with OneTimeProbQuery { val iterations: Int }

Create a One Time belief propagation computer current default universe, with debug information enabled.

13. final def eq(arg0: AnyRef): Boolean
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14. def equals(arg0: Any): Boolean
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15. def finalize(): Unit
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16. final def getClass(): Class[_]
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17. def hashCode(): Int
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18. final def isInstanceOf[T0]: Boolean
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19. def lazyBP(myIterations: Int, depth: Int, upperBounds: Boolean, targets: Element[_]*)(implicit universe: Universe): ProbQueryBeliefPropagation with OneTimeProbabilisticBeliefPropagation with OneTimeProbQuery { val iterations: Int }

Lazy version of BP that operates only on bounds.

20. final def ne(arg0: AnyRef): Boolean
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21. final def notify(): Unit
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22. final def notifyAll(): Unit
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23. def probability[T](target: Element[T], value: T): Double

Use BP to compute the probability that the given element has the given value.

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

Use BP to compute the probability that the given element satisfies the given predicate.

25. final def synchronized[T0](arg0: ⇒ T0): T0
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26. def toString(): String
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27. final def wait(): Unit
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28. final def wait(arg0: Long, arg1: Int): Unit
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29. final def wait(arg0: Long): Unit
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