Packages

  • package root
    Definition Classes
    root
  • package provingground

    This is work towards automated theorem proving based on learning, using homotopy type theory (HoTT) as foundations and natural language processing.

    This is work towards automated theorem proving based on learning, using homotopy type theory (HoTT) as foundations and natural language processing.

    The implementation of homotopy type theory is split into:

    • the object HoTT with terms, types, functions and dependent functions, pairs etc
    • the package induction with general inductive types and recursion/induction on these.

    The learning package has the code for learning.

    Scala code, including the spire library, is integrated with homotopy type theory in the scalahott package

    We have implemented a functor based approach to translation in the translation package, used for nlp as well as serialization and parsing.

    The library package is contains basic structures implemented in HoTT.

    Definition Classes
    root
  • package learning
    Definition Classes
    provingground
  • object NodeCoeffs
    Definition Classes
    learning
  • BaseCons
  • Cons
  • RecCons
  • Target

case class RecCons[State, V, RDom <: HList, Y](headGen: RecursiveGeneratorNodeFamily[RDom, State, Y], headCoeff: V, tail: NodeCoeffs[State, V, RDom, Y]) extends Cons[State, V, RDom, Y] with Product with Serializable

Linear Supertypes
Serializable, Product, Equals, Cons[State, V, RDom, Y], NodeCoeffs[State, V, RDom, Y], AnyRef, Any
Type Hierarchy
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. RecCons
  2. Serializable
  3. Product
  4. Equals
  5. Cons
  6. NodeCoeffs
  7. AnyRef
  8. Any
Implicitly
  1. by any2stringadd
  2. by StringFormat
  3. by Ensuring
  4. by ArrowAssoc
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  2. Show All
Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new RecCons(headGen: RecursiveGeneratorNodeFamily[RDom, State, Y], headCoeff: V, tail: NodeCoeffs[State, V, RDom, Y])

Value Members

  1. def ::(head: (GeneratorNodeFamily[RDom, Y], V)): Cons[State, V, RDom, Y]
    Definition Classes
    NodeCoeffs
  2. def getCoeff[RD <: HList, YY](gen: GeneratorNodeFamily[RD, YY]): Option[V]
    Definition Classes
    Cons → NodeCoeffs
  3. val headCoeff: V
    Definition Classes
    RecCons → Cons
  4. val headGen: RecursiveGeneratorNodeFamily[RDom, State, Y]
    Definition Classes
    RecCons → Cons
  5. val nodeFamilies: Set[GeneratorNodeFamily[RDom, Y]]
    Definition Classes
    RecCons → NodeCoeffs
  6. val output: RandomVarFamily[RDom, Y]
    Definition Classes
    RecCons → NodeCoeffs
  7. def productElementNames: Iterator[String]
    Definition Classes
    Product
  8. val tail: NodeCoeffs[State, V, RDom, Y]
    Definition Classes
    RecCons → Cons
  9. def update[D <: HList, O](data: Value[D, O, V]): NodeCoeffs[State, V, RDom, Y]
    Definition Classes
    NodeCoeffs
  10. def updateAll(dataSeq: Seq[Value[_ <: HList, _, V]]): NodeCoeffs[State, V, RDom, Y]
    Definition Classes
    NodeCoeffs
  11. def updateOpt(data: Value[RDom, Y, V]): Option[RecCons[State, V, RDom, Y]]
    Definition Classes
    RecCons → NodeCoeffs