Packages

object FineDeducer extends Serializable

A refined deducer, i.e., evolution of terms and derivatives of evolution. Various evolutions are defined mutually recursively - of functions, of types, of terms of a type and of all terms. Derivatives are defined mutually recursively with the evolutions.

This is refined so that, for example, arguments are chosen conditionally from the domain of a function.

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Type Members

  1. type SomeFunc = FuncLike[u, v] forSome {type u <: Term with Subs[u], type v <: Term with Subs[v]}

Value Members

  1. def asFuncs(pd: ProbabilityDistribution[Term]): ProbabilityDistribution[SomeFunc]
  2. def asTyps(pd: ProbabilityDistribution[Term]): ProbabilityDistribution[Typ[Term]]
  3. def lambdaEv(varweight: Double)(typEvolve: => (FiniteDistribution[Term]) => ProbabilityDistribution[Term], valueEvolve: => (Term) => (FiniteDistribution[Term]) => ProbabilityDistribution[Term])(p: FiniteDistribution[Term]): ProbabilityDistribution[Option[Term]]

    a lambda-island for evolution:

    a lambda-island for evolution:

    typEvolve

    evolution of types, from which a variable is chosen

    valueEvolve

    evolution of terms, given initial distribution

    p

    initial distribution A type is picked at random, a variable x with this type is generated and mixed in with weight varWeight into the initial distribution p. The evolved distribution is mapped by x :-> _.

  4. def piEv(varweight: Double)(typEvolve: => (FiniteDistribution[Term]) => ProbabilityDistribution[Term], valueEvolve: => (Term) => (FiniteDistribution[Term]) => ProbabilityDistribution[Term])(p: FiniteDistribution[Term]): ProbabilityDistribution[Option[Term]]

    a lambda-island for evolution:

    a lambda-island for evolution:

    typEvolve

    evolution of types, from which a variable is chosen

    valueEvolve

    evolution of terms, given initial distribution

    p

    initial distribution A type is picked at random, a variable x with this type is generated and mixed in with weight varWeight into the initial distribution p. The evolved distribution is mapped by pi(x)(_).

  5. def simpleApplnEv(funcEvolve: => (FiniteDistribution[Term]) => ProbabilityDistribution[SomeFunc], argEvolve: => (Typ[Term]) => (FiniteDistribution[Term]) => ProbabilityDistribution[Term])(p: FiniteDistribution[Term]): ProbabilityDistribution[v forSome {type v <: Term with Subs[v]}]

    evolution by function application, to be used by choosing function at random and then argument conditionally in its domain.

  6. def termClosure(vars: Vector[Term])(fd: FiniteDistribution[Term]): FiniteDistribution[Term]
  7. def typClosure(vars: Vector[Term])(fd: FiniteDistribution[Typ[Term]]): FiniteDistribution[Typ[Term]]
  8. def unif(vars: Term*)(terms: Term*)(axioms: Typ[Term]*): FiniteDistribution[Term]
  9. def unifApplnEv(funcEvolve: => (FiniteDistribution[Term]) => ProbabilityDistribution[SomeFunc], argEvolve: => (FiniteDistribution[Term]) => ProbabilityDistribution[Term])(p: FiniteDistribution[Term]): ProbabilityDistribution[Option[Term]]

    evolution by function application with unification