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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- def asFuncs(pd: ProbabilityDistribution[Term]): ProbabilityDistribution[SomeFunc]
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- def asTyps(pd: ProbabilityDistribution[Term]): ProbabilityDistribution[Typ[Term]]
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- 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 weightvarWeight
into the initial distributionp
. The evolved distribution is mapped byx :-> _
.
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- 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 weightvarWeight
into the initial distributionp
. The evolved distribution is mapped bypi(x)(_)
.
- 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.
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- def termClosure(vars: Vector[Term])(fd: FiniteDistribution[Term]): FiniteDistribution[Term]
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- def typClosure(vars: Vector[Term])(fd: FiniteDistribution[Typ[Term]]): FiniteDistribution[Typ[Term]]
- def unif(vars: Term*)(terms: Term*)(axioms: Typ[Term]*): FiniteDistribution[Term]
- def unifApplnEv(funcEvolve: => (FiniteDistribution[Term]) => ProbabilityDistribution[SomeFunc], argEvolve: => (FiniteDistribution[Term]) => ProbabilityDistribution[Term])(p: FiniteDistribution[Term]): ProbabilityDistribution[Option[Term]]
evolution by function application with unification
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