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# FactoredFrontier 

### Companion class FactoredFrontier

#### object FactoredFrontier

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### Value Members

1. final def !=(arg0: Any): Boolean
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2. final def ##(): Int
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4. def apply(initial: Universe, transition: (Universe) ⇒ Universe, stepTimeMillis: Long)

A Factored Frontier that runs with anytime Belief Propagation.

A Factored Frontier that runs with anytime Belief Propagation.

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 previous.

stepTimeMillis

The time, in milliseconds, for which to run Belief Propagation at each time step.

5. def apply(static: Universe, initial: Universe, transition: (Universe, Universe) ⇒ Universe, stepTimeMillis: Long)

A Factored Frontier that runs with anytime Belief Propagation and a static universe.

A Factored Frontier that runs with anytime Belief Propagation and a static 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.

stepTimeMillis

The time, in milliseconds, for which to run Belief Propagation at each time step.

6. def apply(initial: Universe, transition: (Universe) ⇒ Universe, iterations: Int)

A Factored Frontier that runs with one time Belief Propagation.

A Factored Frontier that runs with one time Belief Propagation.

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 previous.

iterations

The number of iterations with which to run Belief Propagation at each time step.

7. def apply(static: Universe, initial: Universe, transition: (Universe, Universe) ⇒ Universe, iterations: Int)

A Factored Frontier that runs with one time Belief Propagation and a static universe.

A Factored Frontier that runs with one time Belief Propagation and a static 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.

iterations

The number of iterations with which to run Belief Propagation at each time step.

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