Packages

object Deducer extends Serializable

Generating terms from given ones using the main HoTT operations, and the adjoint of this generation. This is viewed as deduction. Generation is a map on probability distributions, but the adjoint regards truncated distributions as the tangent space, and restricts domain to finite distributions.

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Type Members

  1. class HashedUnifInv[U <: Term with Subs[U]] extends (Term) => Set[(U, Term)]
  2. type InvMap = Vector[(Term, Set[(Term, Term)])]

Value Members

  1. def appln(rec: => (ProbabilityDistribution[Term]) => ProbabilityDistribution[Term])(p: ProbabilityDistribution[Term]): ProbabilityDistribution[Option[Term]]

    generating optionally using function application, with function and argument generated recursively; to be mixed in using <+?>

  2. def eqSubs(rec: => (ProbabilityDistribution[Term]) => ProbabilityDistribution[Term])(p: ProbabilityDistribution[Term])(save: (Term, IdentityTyp[Term], Term) => Unit): ProbabilityDistribution[Option[Term with Subs[Term]]]
  3. def feedback(absTheorems: FiniteDistribution[Typ[Term]], absThmsByProofs: FiniteDistribution[Typ[Term]], proofs: Map[Typ[Term], FiniteDistribution[Term]], vars: Vector[Weighted[Term]], lambdaWeight: Double, piWeight: Double): FiniteDistribution[Term]
  4. def flow(fd: FiniteDistribution[Term], shifts: FiniteDistribution[Term]): FiniteDistribution[Term]
  5. def hashedUnifInv[U <: Term with Subs[U]](term: Term, hashedInvMap: Map[ShapeTree, Vector[(Term, Set[(U, Term)])]]): Set[(U, Term)]
  6. def lambda(varweight: Double)(rec: => (ProbabilityDistribution[Term]) => ProbabilityDistribution[Term])(p: ProbabilityDistribution[Term]): ProbabilityDistribution[Option[Term]]

    generating optionally as lambdas, with function and argument generated recursively; to be mixed in using <+?> avoid having value a universe

  7. def lambdaValue[U <: Term with Subs[U]](variable: U): (Term) => Option[Term]

    given a type, returns optionally values of lambda terms with variable of the given type with variable in values from the above variable object

  8. def memAppln(rec: => (ProbabilityDistribution[Term]) => ProbabilityDistribution[Term])(p: ProbabilityDistribution[Term])(save: (Term, Term, Term) => Unit): ProbabilityDistribution[Option[Term]]
  9. def pi(varweight: Double)(rec: => (ProbabilityDistribution[Term]) => ProbabilityDistribution[Term])(p: ProbabilityDistribution[Term]): ProbabilityDistribution[Option[Term]]

    generating optionally as pi's, with function and argument generated recursively; to be mixed in using <+?>

  10. def piValue[U <: Term with Subs[U]](variable: U): (Term) => Option[Term]
  11. def proofEntropies(fd: FiniteDistribution[Term]): Vector[Weighted[Typ[U] forSome {type U >: x$2.type <: Term with Subs[U], val x$2: Term}]]
  12. def unifInv[U <: Term with Subs[U]](term: Term, invMap: Vector[(Term, Set[(U, Term)])]): Set[(U, Term)]
  13. def unpickle(str: String): TermPopulation