abstract class FactoredFrontier extends Filtering with OneTimeFiltering with FFBPHandler
Abstract class that runs the Factored Frontier algorithm. Like a particle filter, the algorithm is supplied with models representing initial and static universes, as well as a universe transition function.
At each time step, the algorithm copies the marginal probabilities for each named element to a new dummy universe. This dummy universe is then supplied to the transition function.
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 FactoredFrontier
 FFBPHandler
 InnerBPHandler
 OneTimeFiltering
 OneTime
 Filtering
 Algorithm
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Instance Constructors

new
FactoredFrontier(static: Universe, initial: Universe, transition: (Universe, Universe) ⇒ Universe)
 static
The universe of elements that do not change over time.
 initial
The universe describing the distribution over the initial state of the system.
 transition
The transition model describing how the current state of the system depends on the static and previous, respectively.
Abstract Value Members

abstract
def
createBP(targets: List[Element[_]], dependentUniverses: List[(Universe, List[NamedEvidence[_]])], dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double, depth: Int = Int.MaxValue, upperBounds: Boolean = false): Unit
Instantiates the appropriate BP algorithm for the current time step.
Instantiates the appropriate BP algorithm for the current time step.
 Attributes
 protected
 Definition Classes
 InnerBPHandler

abstract
def
runBP(): Unit
Runs the BP algorithm at the current time step.
Runs the BP algorithm at the current time step.
 Attributes
 protected
 Definition Classes
 InnerBPHandler
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

val
active: Boolean
 Attributes
 protected
 Definition Classes
 Algorithm

def
advanceTime(evidence: Seq[NamedEvidence[_]] = List()): Unit
Advance the algorithm one time step based on the provided evidence.
Advance the algorithm one time step based on the provided evidence.
 Definition Classes
 FactoredFrontier → Filtering

final
def
asInstanceOf[T0]: T0
 Definition Classes
 Any

val
bp: ProbQueryBeliefPropagation
BP algorithm associated with this time step.
BP algorithm associated with this time step.
 Attributes
 protected[com.cra.figaro]
 Definition Classes
 InnerBPHandler

def
cleanUp(): Unit
Called when the algorithm is killed.
Called when the algorithm is killed. By default, does nothing. Can be overridden.
 Definition Classes
 FactoredFrontier → Algorithm

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

def
computeCurrentDistribution[T](reference: Reference[T]): Stream[(Double, T)]
Returns the distribution over the element referred to by the reference at the current time point.
Returns the distribution over the element referred to by the reference at the current time point.
 Definition Classes
 FactoredFrontier → Filtering

def
computeCurrentExpectation[T](reference: Reference[T], function: (T) ⇒ Double): Double
Returns the expectation of the element referred to by the reference under the given function at the current time point.
Returns the expectation of the element referred to by the reference under the given function at the current time point.
 Definition Classes
 FactoredFrontier → Filtering

def
computeCurrentProbability[T](reference: Reference[T], predicate: (T) ⇒ Boolean): Double
Returns the probability that the element referred to by the reference satisfies the given predicate at the current time point.
Returns the probability that the element referred to by the reference satisfies the given predicate at the current time point.
 Attributes
 protected
 Definition Classes
 Filtering

def
currentDistribution[T](reference: Reference[T]): Stream[(Double, T)]
Returns the distribution over the element referred to by the reference at the current time point.
Returns the distribution over the element referred to by the reference at the current time point.
 Definition Classes
 OneTimeFiltering → Filtering

def
currentExpectation[T](reference: Reference[T], function: (T) ⇒ Double): Double
Returns the expectation of the element referred to by the reference under the given function at the current time point.
Returns the expectation of the element referred to by the reference under the given function at the current time point.
 Definition Classes
 OneTimeFiltering → Filtering

def
currentProbability[T](reference: Reference[T], predicate: (T) ⇒ Boolean): Double
Returns the probability that the element referred to by the reference satisfies the given predicate at the current time point.
Returns the probability that the element referred to by the reference satisfies the given predicate at the current time point.
 Definition Classes
 OneTimeFiltering → Filtering

def
currentProbability[T](reference: Reference[T], value: T): Double
Returns the probability that the element referred to by the reference produces the given value at the current time point.
Returns the probability that the element referred to by the reference produces the given value at the current time point.
 Definition Classes
 Filtering

var
currentStatic: Universe
 Attributes
 protected
 Definition Classes
 FactoredFrontier → FFBPHandler

val
currentUniverse: Universe
Universe associated with this algorithm.
Universe associated with this algorithm.
 Attributes
 protected
 Definition Classes
 InnerBPHandler
 val dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double
 val dependentUniverse: List[Nothing]

def
doKill(): Unit
 Attributes
 protected[com.cra.figaro.algorithm]
 Definition Classes
 OneTime → Algorithm

def
doResume(): Unit
 Attributes
 protected[com.cra.figaro.algorithm]
 Definition Classes
 OneTime → Algorithm

def
doStart(): Unit
 Attributes
 protected[com.cra.figaro.algorithm]
 Definition Classes
 OneTime → Algorithm

def
doStop(): Unit
 Attributes
 protected[com.cra.figaro.algorithm]
 Definition Classes
 OneTime → Algorithm

final
def
eq(arg0: AnyRef): Boolean
 Definition Classes
 AnyRef

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

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
getNamedElements(u: Universe): List[Element[_]]
Returns all named elements in this universe.
Returns all named elements in this universe.
 Attributes
 protected
 Definition Classes
 FFBPHandler

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
 FactoredFrontier → 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

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

final
def
notify(): Unit
 Definition Classes
 AnyRef

final
def
notifyAll(): Unit
 Definition Classes
 AnyRef

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
run(): Unit
Run the algorithm, performing its computation to completion.
Run the algorithm, performing its computation to completion.
 Definition Classes
 FactoredFrontier → OneTime

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

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( ... )