Packages

package learning

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Type Members

  1. trait AdjDiffbleFunction[A, B] extends AnyRef
  2. case class AnswerFromPost[P, U, W, ID](func: (P) => U)(implicit pw: Postable[P, W, ID]) extends Product with Serializable

    Looking up an answer to a query for U from posts of type P meant for querying for the latest post etc.

    Looking up an answer to a query for U from posts of type P meant for querying for the latest post etc.

    func

    transformation of the content of the post

    pw

    postability

  3. trait ApplnInverse extends AnyRef

    inverses under application with an without unification

  4. class BackPaths[A] extends AnyRef
  5. case class BasicDeducer(applnWeight: Double = 0.2, lambdaWeight: Double = 0.2, piWeight: Double = 0.2, varWeight: Double = 0.3, vars: Vector[Term] = Vector()) extends Product with Serializable
  6. trait BiPostable[P, W, ID] extends Postable[P, W, ID]
  7. case class BufferedRun[A](iter: Iterator[A]) extends Product with Serializable
  8. trait BuffersJson[W, B] extends AnyRef
  9. trait BuildPostable[W, B, P] extends AnyRef

    typeclass for building HLists of postables (and other things) based on HLists of buffers, but formally just returns object of type P

  10. trait BuildQuery[Q, W, ID, PList <: HList] extends AnyRef
  11. case class Collated[P](contents: Vector[P]) extends Product with Serializable
  12. class CompositeProver[D] extends AnyRef
  13. trait Conditioning[D[_]] extends AnyRef

    typeclass for being able to condition

  14. trait ContextExport[Boat, D[_]] extends AnyRef

    changes in the distribution-like object other than those induced by object level map while exporting from an island typically a change in context for variables representing terms in a context

    changes in the distribution-like object other than those induced by object level map while exporting from an island typically a change in context for variables representing terms in a context

    Boat

    the boat for an island

    D

    the distribution-like object

  15. class CounterGlobalID extends GlobalID[(Int, Int)]

    allows posting globally and keeps count without stroing anything

  16. trait DataGetter[P, W, ID] extends AnyRef
  17. case class Deducer(applnWeight: Double = 0.2, lambdaWeight: Double = 0.2, piWeight: Double = 0.2, varWeight: Double = 0.3, vars: Vector[Weighted[Term]] = Vector(), propDecay: Double = 0.5, cutoff: Double = 0.01, feedbackScale: Double = 0.1, abstractionWeight: Double = 0.3, genMemory: Double = 0.8) extends Product with Serializable
  18. class DeducerBuffer extends AnyRef
  19. class DeducerSource extends AnyRef
  20. class DerivedEquations extends AnyRef
  21. trait DiffbleFunction[A, B] extends (A) => B
  22. trait DistributionState[State, D[_]] extends StateDistribution[State, D]

    typeclass for providing distributions from a state and modifying a state from distributions

  23. class DistributionStateEvolver[State, D[_]] extends StateEvolver[State]
  24. case class EgUnif(n: Int) extends Product with Serializable
  25. trait Empty[D[_]] extends AnyRef
  26. case class EntropyAtomWeight(h0: Double, kl0: Double, p0: Double, q0: Double, initWeight: Double, hW: Double, klW: Double, crossKL: Boolean = true) extends Product with Serializable

    Spire gradient learning for tradeoff between generation entropy and theorem-proof relative entropy

    Spire gradient learning for tradeoff between generation entropy and theorem-proof relative entropy

    h0

    the initial generation entropy

    kl0

    the initial relative entropy between theorems and proofs

    p0

    the initial theorem weight of the element

    q0

    the initial proof weight of the element

    initWeight

    the weight of the initial distribution in generation of terms

  27. case class EqDistMemo[State](varDists: Map[(State, RandomVar[_]), (Double, FiniteDistribution[_], Set[EquationNode])], nodeDists: Map[(State, GeneratorNode[_]), (Double, FiniteDistribution[_], Set[EquationNode])]) extends Product with Serializable
  28. case class Equation(lhs: Expression, rhs: Expression) extends Product with Serializable
  29. class EquationExporter extends AnyRef
  30. case class EquationNode(lhs: Expression, rhs: Expression) extends Product with Serializable
  31. abstract class ErasablePostBuffer[P, ID] extends GlobalPost[P, ID]
  32. trait EvolvedEquations[State] extends AnyRef
  33. case class EvolvedState(init: TermState, result: TermState, params: TermGenParams, epsilon: Double) extends EvolvedStateLike with Product with Serializable
  34. trait EvolvedStateLike extends AnyRef
  35. class EvolverEquations[F] extends AnyRef

    variables for probabilities and equations for consistency

  36. trait EvolverSupport extends AnyRef

    Support of the final distribution of an evolver, i.e., a generative model for terms

  37. sealed trait EvolverVariables extends AnyRef

    Variables in an evolver; not all need to be used in a give case

  38. sealed trait Expression extends AnyRef
  39. class ExpressionEquationIndexifier extends AnyRef

    Maps equations based on expressions in terms, randomvariables etc.

    Maps equations based on expressions in terms, randomvariables etc. to equations based on indices only, for rapid computation. Also provides some helpers to relate index combinations and expressions.

  40. trait ExpressionEquationSolver extends AnyRef

    Solve equations based on expressions (approximately), and compute various related quantities The actual solving is done after translating the equations to ones based on indices, for the sake of efficiency.

    Solve equations based on expressions (approximately), and compute various related quantities The actual solving is done after translating the equations to ones based on indices, for the sake of efficiency. Other methods let one construct new expression-equation-solvers, including by export.

  41. trait ExstParMap extends AnyRef
  42. trait FallBackLookups extends AnyRef
  43. class FatExprEquations extends ExpressionEquationIndexifier
  44. case class FineDeducer(applnWeight: Double = 0.1, lambdaWeight: Double = 0.1, piWeight: Double = 0.1, varWeight: Double = 0.3, unifyWeight: Double = 0.5) extends FineEvolver with Product with Serializable

    A refined deducer, i.e., evolution of terms and derivatives of evolution.

    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, of type families 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.

    varWeight

    weight of a variable inside a lambda

  45. class FineDeducerStep[X[_]] extends AnyRef

    Monad based step for deducer, to be used, for example, with Monix Task

  46. class FineEvolver extends AnyRef

    A refined evolver, i.e., evolution of terms and subclasses such as types.

    A refined evolver, i.e., evolution of terms and subclasses such as types. Various evolutions are defined mutually recursively - of functions, of types, of terms of a type, of type families 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.

  47. class ForceDirected[A, V] extends AnyRef
  48. case class ForceDirectedVectors[A](vertices: Set[A], edges: Map[(A, A), Double], coulomb: Double, elasticity: Double, dim: Int, R: Double, scale: Double, decay: Double, steps: Int) extends ForceDirected[A, Vector[Double]] with Product with Serializable
  49. case class GatherMapPost[P](contents: Set[P]) extends Product with Serializable
  50. case class GatherPost[P](contents: Set[P]) extends Product with Serializable
  51. abstract class GenMonixFiniteDistribution[State] extends AnyRef
  52. abstract class GenMonixFiniteDistributionEq[State] extends AnyRef
  53. abstract class GenTruncatedFiniteDistribution[State] extends AnyRef
  54. case class GeneratorData[V](nodeCoeffs: Vector[(GeneratorNodeFamily[_ <: HList, _], V)], varsToResolve: Vector[RandomVar[_]]) extends Product with Serializable
  55. case class GeneratorEquations[State](nodeCoeffSeq: NodeCoeffSeq[State, Double], varWeight: Double, initState: State, finalState: State)(implicit sd: StateDistribution[State, FiniteDistribution]) extends EvolvedEquations[State] with Product with Serializable
  56. sealed trait GeneratorNode[+O] extends GeneratorNodeFamily[HNil, O]

    A formal node for describing recursive generation.

    A formal node for describing recursive generation. Can have several inputList, encoded as an HList, but has just one output.

  57. sealed trait GeneratorNodeFamily[Dom <: HList, +O] extends AnyRef

    Family of (recursive) generation functions, either a function giving a family or a single {{GeneratorNode}}, which is the interesting case.

  58. case class GeneratorTF[State](nodeCoeffSeq: NodeCoeffSeq[State, Double], varWeight: Double, initState: State, finalState: State)(implicit sd: StateDistribution[State, FiniteDistribution]) extends Product with Serializable
  59. case class GeneratorVariables[State](nodeCoeffSeq: NodeCoeffSeq[State, Double], state: State)(implicit sd: StateDistribution[State, FiniteDistribution]) extends Product with Serializable

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    State

    scala type of the initial state

    nodeCoeffSeq

    the various generator nodes with coefficients for various random variables and families

    sd

    finite distributions from the initial state corresponding to random variables and families

  60. trait GlobalID[ID] extends AnyRef
  61. trait GlobalPost[P, ID] extends AnyRef

    Allows posting any content, typically just returns an ID to be used by something else.

  62. class GraphEmbeddingLogisitic extends AnyRef
  63. trait HistoryGetter[W, B, ID] extends AnyRef
  64. class HoTTPostWeb extends AnyRef

    Better building of post webs, without depending on separate lists for implicits and history (history to be done).

  65. class HoTTWebSession extends SimpleSession[HoTTPostWeb, (Int, Int)]
  66. class IndexEquationMapSolver extends ExpressionEquationIndexifier

    Seek an approximately stable distribution for equations given in terms of indices, hence solving the equations (approximately).

    Seek an approximately stable distribution for equations given in terms of indices, hence solving the equations (approximately). Here stable distribution is under the iteration to solve equations viewing them as fixed points. This is an implementation based on maps and keeping track of supports, which is not used as Vectors were more efficient.

  67. class IndexEquationSolver extends ExpressionEquationIndexifier

    Seek an approximately stable distribution for equations given in terms of indices, hence solving the equations (approximately).

    Seek an approximately stable distribution for equations given in terms of indices, hence solving the equations (approximately). Here stable distribution is under the iteration to solve equations viewing them as fixed points. A few quantitites related to the solutions, or the equations themselves, are also computed.

  68. class IndexedBacktrace extends AnyRef

    Computation of probabilities of elements in equations for other elements, and of upper bounds on distances, based on equations in indices.

  69. case class IntElem(n: Int) extends SequenceElement with Product with Serializable
  70. trait IterantRunner[S, A, M] extends AnyRef
  71. case class LatestAnswer[Q, W, ID](answers: Vector[AnswerFromPost[_, Q, W, ID]])(implicit h: PostHistory[W, ID]) extends LocalQueryable[Q, W, ID] with Product with Serializable

    Queries answered by taking the latest out of possibly many choices of posts to be looked up and transformed.

    Queries answered by taking the latest out of possibly many choices of posts to be looked up and transformed.

    answers

    various ways in which the query can be answered

    h

    the history

  72. case class LatestTagged[Q, W, ID]()(implicit tag: scala.reflect.api.JavaUniverse.TypeTag[Q], h: PostHistory[W, ID]) extends LocalQueryable[Q, W, ID] with Product with Serializable
  73. case class LocalProver(initState: TermState = TermState(FiniteDistribution.empty, FiniteDistribution.empty), tg: TermGenParams = TermGenParams(), cutoff: Double = math.pow(10, -4), genMaxDepth: Option[Int] = None, limit: FiniteDuration = 12.minutes, maxRatio: Double = 1.01, resolution: Double = 0.0, scale: Double = 1.0, steps: Int = 10000, maxDepth: Int = 10, hW: Double = 1, klW: Double = 1, smoothing: Option[Double] = None, relativeEval: Boolean = false, stateFromEquation: Boolean = false, exponent: Double = 0.5, decay: Double = 1, maxTime: Option[Long] = None) extends LocalProverStep with Product with Serializable

    Collect local/generative/tactical proving; this includes configuration and learning but excludes strategy and attention.

    Collect local/generative/tactical proving; this includes configuration and learning but excludes strategy and attention. This can be called in a loop generating goals based on unproved theorems, using representation/deep learning with attention focussed or interactively.

  74. trait LocalProverStep extends AnyRef
  75. trait LocalQueryable[U, W, ID] extends AnyRef

    Typeclass for being able to query W for a vector of elements of type Q at an index

  76. case class LocalTangentProver(initState: TermState = TermState(FiniteDistribution.empty, FiniteDistribution.empty), initEquations: Set[EquationNode], tangentState: TermState, tg: TermGenParams = TermGenParams(), cutoff: Double = math.pow(10, -4), genMaxDepth: Option[Int] = None, limit: FiniteDuration = 3.minutes, maxRatio: Double = 1.01, resolution: Double = 0.0, scale: Double = 1.0, steps: Int = 10000, maxDepth: Int = 10, hW: Double = 1, klW: Double = 1, smoothing: Option[Double] = None, relativeEval: Boolean = false, stateFromEquation: Boolean = false, exponent: Double = 0.5, decay: Double = 1, maxTime: Option[Long] = None) extends LocalProverStep with Product with Serializable
  77. case class MemoState[D[_], V, C](randVarVals: Set[Value[_, D]], genData: GeneratorData[V], context: C) extends Product with Serializable
  78. case class MonixFiniteDistribution[State](nodeCoeffSeq: NodeCoeffSeq[State, Double], varWeight: Double)(implicit sd: StateDistribution[State, FiniteDistribution]) extends GenMonixFiniteDistribution[State] with Product with Serializable

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    State

    scala type of the initial state

    nodeCoeffSeq

    the various generator nodes with coefficients for various random variables and families

    sd

    finite distributions from the initial state corresponding to random variables and families

  79. case class MonixFiniteDistributionEq[State](nodeCoeffSeq: NodeCoeffSeq[State, Double], varWeight: Double, limit: FiniteDuration = 3.minutes)(implicit sd: StateDistribution[State, FiniteDistribution]) extends GenMonixFiniteDistributionEq[State] with Product with Serializable

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    State

    scala type of the initial state

    nodeCoeffSeq

    the various generator nodes with coefficients for various random variables and families

    sd

    finite distributions from the initial state corresponding to random variables and families

  80. trait MonixSamples extends Samples[Task]
  81. case class MonixTangentFiniteDistribution[State](nodeCoeffSeq: NodeCoeffSeq[State, Double], varWeight: Double, baseState: State)(implicit sd: StateDistribution[State, FiniteDistribution]) extends GenMonixFiniteDistribution[State] with Product with Serializable

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    State

    scala type of the initial state

    nodeCoeffSeq

    the various generator nodes with coefficients for various random variables and families

    sd

    finite distributions from the initial state corresponding to random variables and families

  82. case class MonixTangentFiniteDistributionEq[State](nodeCoeffSeq: NodeCoeffSeq[State, Double], varWeight: Double, baseState: State, baseEquations: Set[EquationNode], limit: FiniteDuration = 3.minutes)(implicit sd: StateDistribution[State, FiniteDistribution]) extends GenMonixFiniteDistributionEq[State] with Product with Serializable

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    State

    scala type of the initial state

    nodeCoeffSeq

    the various generator nodes with coefficients for various random variables and families

    sd

    finite distributions from the initial state corresponding to random variables and families

  83. case class NextSample(p: FiniteDistribution[Term], ded: FineDeducer = FineDeducer(), vars: Vector[Term] = Vector(), size: Int = 1000, derTotalSize: Int = 1000, epsilon: Double = 0.2, inertia: Double = 0.3) extends Product with Serializable
  84. sealed trait NodeCoeffSeq[State, V] extends AnyRef
  85. sealed trait NodeCoeffs[State, V, RDom <: HList, Y] extends AnyRef
  86. class ParDistEq extends RecParDistEq
  87. class ParDistEqMemo extends AnyRef
  88. case class ParMapState(termDist: ParMap[Term, Double], typDist: ParMap[Typ[Term], Double], vars: Vector[Term] = Vector(), inds: ParMap[ExstInducDefn, Double] = ParMap(), goalDist: ParMap[Typ[Term], Double] = ParMap(), context: Context = Context.Empty) extends Product with Serializable
  89. class ParTangentDistEq extends RecParDistEq
  90. case class ParTermState(ts: TermState) extends Product with Serializable
  91. case class PickledTermPopulation(termsByType: Map[String, Vector[PickledWeighted]], types: Vector[PickledWeighted], thmsByProofs: Vector[PickledWeighted], vars: Vector[PickledWeighted], lambdaWeight: Double, piWeight: Double) extends Product with Serializable
  92. abstract class PostBuffer[P, ID] extends GlobalPost[P, ID]

    A buffer for storing posts, extending GlobalPost which supplies an ID

  93. case class PostData[P, W, ID](content: P, id: ID)(implicit pw: Postable[P, W, ID]) extends Product with Serializable

    Data for a post, including the implicit saying it is postable

    Data for a post, including the implicit saying it is postable

    content

    the content of the post

    id

    the index of the post, returned after posting

  94. trait PostDiscarder[P, ID] extends GlobalPost[P, ID]
  95. trait PostHistory[W, ID] extends AnyRef
  96. sealed trait PostMaps[P] extends AnyRef
  97. sealed trait PostResponse[W, ID] extends AnyRef

    Response to a post, generating one or more posts or just a callback; this exists mainly for nicer type collections.

  98. trait Postable[P, W, ID] extends AnyRef

    Typeclass for being able to post with content type P in W

  99. case class PreviousPosts[P](contents: Vector[P]) extends Product with Serializable
  100. case class ProductIndexExpression(constant: Double, indices: Vector[Int], negIndices: Vector[Int]) extends Product with Serializable
  101. case class ProofEntropies(gens: Map[Term, Double], theorems: Map[Typ[Term], Double], proofs: Map[Term, Double], genWeight: Double) extends Product with Serializable
  102. case class QueryBaseState(init: TermState) extends Product with Serializable
  103. case class QueryEquations(equations: Set[Equation]) extends Product with Serializable
  104. sealed trait QueryFromPosts[Q, PList <: HList] extends AnyRef
  105. case class QueryInitState(init: TermState) extends Product with Serializable
  106. case class QueryOptions[Q, W, ID](answers: (PostData[_, W, ID]) => Option[Q], modifiers: (PostData[_, W, ID]) => (Q) => Q) extends Product with Serializable
  107. case class QueryProver(lp: LocalProver) extends Product with Serializable
  108. trait Queryable[U, W] extends AnyRef

    Typeclass for being able to query W for type Q

  109. class RandomVar[+O] extends RandomVarFamily[HNil, O]

    A formal Random Variable up to equality of distribution.

    A formal Random Variable up to equality of distribution. May actually have representations instead of distributions, for example.

  110. class RandomVarFamily[Dom <: HList, +O] extends AnyRef

    A formal family of Random Variables up to equality of distribution.

    A formal family of Random Variables up to equality of distribution. May actually have representations instead of distributions, for example.

  111. sealed trait RandomVarList[U <: HList] extends AnyRef

    List of random variables, e.g.

    List of random variables, e.g. input of simple generator nodes.

  112. abstract class RandomVarMemo[D[_]] extends RandomVarValues[D]
  113. trait RandomVarValues[D[_]] extends AnyRef
  114. case class RandomVector[X](base: RandomVar[X]) extends RandomVar[Vector[X]] with Product with Serializable

    distributions of vectors from a base distribution

    distributions of vectors from a base distribution

    X

    scala type of the base

    base

    the base distribution

  115. trait RecParDistEq extends AnyRef
  116. sealed trait RecursiveGeneratorNode[State, +O] extends GeneratorNode[O] with RecursiveGeneratorNodeFamily[HNil, State, O]
  117. sealed trait RecursiveGeneratorNodeFamily[Dom <: HList, State, +O] extends GeneratorNodeFamily[Dom, O]
  118. final case class Representation[T](rep: Vector[WeightVect[T]]) extends AnyVal with Product with Serializable
  119. class RepresentationLearner[A] extends AnyRef
  120. trait Samples[X[_]] extends TangSamples[X]
  121. trait SimpleDataGetter extends AnyRef
  122. class SimpleSession[W, ID] extends AnyRef

    A simple session to post stuff, call responses and if these responses generate posts, recursively call itself for them.

  123. case class SnapShot[X, P](state: X, name: String, loops: Int, param: P) extends Product with Serializable
  124. case class SomePost[P](content: P) extends Product with Serializable

    Wrapper to query for all posts, even after the query position or in a different thread

    Wrapper to query for all posts, even after the query position or in a different thread

    content

    the wrapped content

  125. sealed trait Sort[-S, +T] extends AnyRef

    A sort, i.e.

    A sort, i.e. type refining a scala type. Can also be used for conditioning, giving one distribution from another.

    T

    scala type elements of this Sort

  126. sealed trait SortList[U <: HList] extends AnyRef

    List of Sorts, used as domains for families.

  127. class SpireExprEquations extends ExpressionEquationIndexifier
  128. case class SpireGradient(vars: Vector[Expression], p: Map[Expression, Double], cost: Expression) extends Product with Serializable
  129. case class SplitPost[P, Q, W, ID](content: P, transformation: (Q) => P)(implicit evidence$10: scala.reflect.api.JavaUniverse.TypeTag[P], evidence$11: scala.reflect.api.JavaUniverse.TypeTag[Q], evidence$12: scala.reflect.api.JavaUniverse.TypeTag[W], evidence$13: scala.reflect.api.JavaUniverse.TypeTag[ID], pw: Postable[P, W, ID], qq: LocalQueryable[Q, W, ID]) extends Product with Serializable

    Wrapper for post content that should be posted, with the previous elements of the same type also posted, in general with transformations (e.g.

    Wrapper for post content that should be posted, with the previous elements of the same type also posted, in general with transformations (e.g. rescale)

    content

    the content to be posted

    transformation

    transformations of other posts, typically rescaling

    pw

    postability of P

  130. trait StateDistribution[State, D[_]] extends AnyRef

    typeclass for providing distributions from a state

  131. trait StateEvolver[State] extends AnyRef
  132. class StochasticLang[E] extends TruncatedDistributionLang[E]
  133. case class SumIndexExpression(terms: Vector[ProductIndexExpression]) extends Product with Serializable
  134. trait Support[D[_]] extends AnyRef
  135. case class TFData(vars: Map[VarVal[_], Double], varSets: Set[Set[VarVal[_]]], inFinalEvent: Map[Variable[_], Set[Variable[_]]], inFinalPairEvent: Map[Variable[_], Set[(Variable[_], Variable[_])]], equations: Set[Equation]) extends Product with Serializable
  136. case class TFDist[A](pmfMap: Map[A, Output[Double]]) extends Product with Serializable
  137. class TFEg extends AnyRef
  138. trait TangSamples[X[_]] extends AnyRef
  139. case class TangVec[+A](point: A, vec: A) extends Product with Serializable
  140. case class TangentFiniteDistribution[State](baseState: State, nodeCoeffSeq: NodeCoeffSeq[State, Double], varWeight: Double)(implicit sd: StateDistribution[State, FiniteDistribution]) extends GenTruncatedFiniteDistribution[State] with Product with Serializable

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    State

    scala type of the initial state

    nodeCoeffSeq

    the various generator nodes with coefficients for various random variables and families

    sd

    finite distributions from the initial state corresponding to random variables and families

  141. class TensorFlowExprEquations extends ExpressionEquationIndexifier
  142. class TensorFlowExprVarEquations extends ExpressionEquationIndexifier
  143. class TensorFlowFatExprEquations extends FatExprEquations
  144. case class TensorflowExpressions(tf: Ops, init: PartialFunction[Expression, Operand[TFloat32]]) extends Product with Serializable
  145. class TermBucket extends AnyRef
  146. trait TermEvolution extends AnyRef
  147. class TermEvolutionStep[X[_]] extends AnyRef
  148. class TermEvolver extends TermEvolution
  149. case class TermGenCost(ge: EvolvedEquations[TermState], varWeight: Double, hW: Double = 1, klW: Double = 1, eqW: Double = 1, epsilon: Double = math.pow(10, -5)) extends TermGenEqCost with Product with Serializable
  150. abstract class TermGenEqCost extends AnyRef
  151. case class TermGenParams(appW: Double = 0.1, unAppW: Double = 0.1, argAppW: Double = 0.1, lmW: Double = 0.1, piW: Double = 0.1, piTermW: Double = 0, termsByTypW: Double = 0.05, typFromFamilyW: Double = 0.05, sigmaW: Double = 0.05, recDefW: Double = 0, inducDefW: Double = 0, typAsCodW: Double = 0.05, targetInducW: Double = 0, varWeight: Double = 0.3, goalWeight: Double = 0.7, typVsFamily: Double = 0.5, negTargetW: Double = 0, solverW: Double = 0, contraW: Double = 0, solver: TypSolver = TypSolver.coreSolver) extends TermNodeCoeffSeq[TermState] with Product with Serializable
  152. case class TermGenParamsNodes(tg: TermGenParams) extends TermGeneratorNodes[TermState] with Product with Serializable
  153. class TermGeneratorNodes[InitState] extends AnyRef

    Combining terms and subclasses to get terms, types, functions etc; these are abstract specifications, to be used for generating distributions, obtaining equations etc.

    Combining terms and subclasses to get terms, types, functions etc; these are abstract specifications, to be used for generating distributions, obtaining equations etc.

    InitState

    the initial state for the dynamics, equations etc

  154. case class TermLearner[F](supp: EvolverSupport, prob: (EvolverVariables) => F, apInv: ApplnInverse)(implicit evidence$3: Field[F], evidence$4: Trig[F]) extends EvolverEquations[F] with Product with Serializable

    Adding equations from a simple generative model to EvolverEquations

  155. abstract class TermNodeCoeffSeq[State] extends AnyRef
  156. case class TermPopulation(termsByType: Map[Typ[Term], FiniteDistribution[Term]], types: FiniteDistribution[Typ[Term]], thmsByProofs: FiniteDistribution[Typ[Term]], vars: Vector[Weighted[Term]], lambdaWeight: Double, piWeight: Double, applnInvMap: InvMap = Vector()) extends Product with Serializable
  157. case class TermState(terms: FiniteDistribution[Term], typs: FiniteDistribution[Typ[Term]], vars: Vector[Term] = Vector(), inds: FiniteDistribution[ExstInducDefn] = FD.empty[ExstInducDefn], goals: FiniteDistribution[Typ[Term]] = FD.empty, context: Context = Context.Empty) extends TermsTypThms with Product with Serializable

    A state, typically the initial state, for generating terms, types etc

    A state, typically the initial state, for generating terms, types etc

    terms

    distribution of terms

    typs

    distribution of types

    vars

    variables, over which we may take closures

    inds

    inductive type definitions

  158. trait TermsTypThms extends AnyRef
  159. case class TheoremFeedback(fd: FiniteDistribution[Term], tfd: FiniteDistribution[Typ[Term]], vars: Vector[Term] = Vector(), scale: Double = 1.0, thmScale: Double = 0.3, thmTarget: Double = 0.2) extends Product with Serializable

    feedback based on the term-type map as well as ensuring total weight of theorems is not small; various steps are explicit for exploration and debugging

  160. case class ThmEntropies(fd: FiniteDistribution[Term], varNames: Vector[Term] = Vector(), scale: Double = 1.0, thmScale: Double = 0.3, thmTarget: Double = 0.2) extends Product with Serializable
  161. final case class TruncDistVal[A](getFD: (Double) => Option[FiniteDistribution[A]]) extends AnyVal with Product with Serializable
  162. sealed trait TruncatedDistribution[A] extends AnyRef
  163. class TruncatedDistributionDomain[E] extends Domain[TruncatedDistribution[E]]
  164. class TruncatedDistributionExprPatterns[E] extends ExprPatterns[TruncatedDistribution[E]]
  165. class TruncatedDistributionLang[E] extends ExprLang[TruncatedDistribution[E]]
  166. case class TruncatedFiniteDistribution[State](nodeCoeffSeq: NodeCoeffSeq[State, Double], varWeight: Double)(implicit sd: StateDistribution[State, FiniteDistribution]) extends GenTruncatedFiniteDistribution[State] with Product with Serializable

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    resolving a general specification of a recursive generative model as finite distributions, depending on truncation; the coefficients of the various generator nodes should be Double

    State

    scala type of the initial state

    nodeCoeffSeq

    the various generator nodes with coefficients for various random variables and families

    sd

    finite distributions from the initial state corresponding to random variables and families

  167. trait TypSolver extends (Typ[Term]) => Option[Term]
  168. sealed abstract class TypedPostResponse[P, W, ID] extends PostResponse[W, ID]

    Post response with type P of post as a type parameter

  169. case class VarValueSet[D[_]](randVarVals: Set[Value[_, D]], randVarFamilyVals: Set[Value[_ <: HList, _, D]]) extends Product with Serializable
  170. case class WebState[W, ID](web: W, apexPosts: Vector[PostData[_, W, ID]] = Vector()) extends Product with Serializable
  171. case class WeightVect[T](elem: T, vect: Vector[Double]) extends Product with Serializable
  172. case class WeightedBackPaths[A, C](gens: Map[A, Vector[(C, Vector[A])]], coeffWeights: (C) => Double) extends BackPaths[A] with Product with Serializable
  173. case class WeightedBiPaths[A, C](gens: Map[A, Vector[(C, Vector[A])]], forwardGens: Map[A, Vector[(C, A)]], coeffWeights: (C) => Double, backWeight: Double) extends BackPaths[A] with Product with Serializable
  174. class WeightedTermBucket extends AnyRef

Deprecated Type Members

  1. case class ErasableWebBuffer[P, ID](buffer: ErasablePostBuffer[P, ID])(implicit pw: Postable[P, HoTTPost, ID]) extends Product with Serializable
    Annotations
    @deprecated
    Deprecated

    (Since version soon) using HoTTPostWeb

  2. sealed trait GlobalProver[R] extends AnyRef
    Annotations
    @deprecated
    Deprecated

    (Since version now) use composite prover

  3. class HoTTPost extends AnyRef
    Annotations
    @deprecated
    Deprecated

    (Since version soon) migrating to HoTTPostWeb

  4. class QueryImplicit[Q, PList <: HList] extends QueryImplicitWrap[Q, Q, PList]
    Annotations
    @deprecated
    Deprecated

    (Since version now) define query-from-posts and lift

  5. class QueryImplicitWrap[Q, T, PList <: HList] extends AnyRef

    Have a wrapper type T for the query and make the companion object extend this class, giving query-from-posts as input (whose type should be deducable)

    Have a wrapper type T for the query and make the companion object extend this class, giving query-from-posts as input (whose type should be deducable)

    Annotations
    @deprecated
    Deprecated

    (Since version now) define query-from-posts and lift

  6. case class WebBuffer[P, ID](buffer: PostBuffer[P, ID])(implicit pw: Postable[P, HoTTPost, ID]) extends Product with Serializable
    Annotations
    @deprecated
    Deprecated

    (Since version soon) using HoTTPostWeb

Value Members

  1. object AdjDiffbleFunction
  2. object ApplnInverse
  3. object BuffersJson
  4. object BuildPostable
  5. object BuildQuery
  6. case object Conditioning extends Product with Serializable
  7. object ContextExport
  8. object DE extends DerivedEquations
  9. object DataGetter extends SimpleDataGetter
  10. object Deducer extends Serializable

    Generating terms from given ones using the main HoTT operations, and the adjoint of this generation.

    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.

  11. object DeducerSource
  12. object DerivedEquations
  13. object DiffbleFunction
  14. object DistributionState
  15. object Empty
  16. object EntropyAtomWeight extends Serializable
  17. object EqDistMemo extends Serializable
  18. object EquationExporter
  19. object EquationNode extends Serializable
  20. object EquationOps
  21. object ErasablePostBuffer
  22. object EvolverEquations
  23. object EvolverVariables
  24. object Expression
  25. object ExpressionEquationIndexifier
  26. object ExpressionEquationSolver

    Working with expressions built from initial and final values of random variables, including in islands, given equations satisfied by these

  27. object ExstParMap
  28. object FieldGramSchmidt
  29. object FineDeducer extends Serializable

    A refined deducer, i.e., evolution of terms and derivatives of evolution.

    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.

  30. object FineDeducerStep
  31. object FineProverTasks

    A collection of functions to build provers; some are abstract methods for exploring, searching etc., while others generate terms and types, sometimes as derivatives.

    A collection of functions to build provers; some are abstract methods for exploring, searching etc., while others generate terms and types, sometimes as derivatives. Some methods combine the two to give a ready to use function. These are based on TermEvolver and Monix.

  32. object FiniteDistributionLearner

    A combinator for learning systems with state finite distributions on vertices.

    A combinator for learning systems with state finite distributions on vertices. Systems are built from components labeled by elements of a set M. The state also has weights for these components. The components are built from: moves (partial functions), partial combinations and islands.

  33. object GeneratorNode
  34. object GeneratorNodeFamily
  35. object GeneratorTF extends Serializable
  36. object GeneratorVariables extends Serializable
  37. object GeometricDistribution

    An example, the geometric distribution in an abstract form

  38. object GramSchmidt
  39. object GraphEmbedding
  40. object HistoryGetter
  41. object HoTTBot
  42. object HoTTMessages

    Messages to be posted for autonomous/interactive running.

    Messages to be posted for autonomous/interactive running. These can be posted by a user, rule-based bot or a deep-learning system; from the point of view of deep learning, these are moves.

    Some messages are instructions for what to do next; some report results and some provide data for use in the future.

    Some types like LocalProver, ExpressionEval, TermGenParams etc can be posted in their raw form.

  43. object HoTTPost
  44. object HoTTPostWeb
  45. object HoTTWebSession
  46. object HoTTgen
  47. object Hub
  48. object IndexEquationSolver
  49. object IndexedBacktrace
  50. object IterantRunner
  51. object IterateDyn
  52. object LemmaWeigths
  53. object LocalProver extends Serializable
  54. object LocalQueryable extends FallBackLookups
  55. object LocalTangentProver extends Serializable
  56. object MapVS
  57. object MemoState extends Serializable
  58. object MonixFieldGramSchmidt
  59. object MonixFiniteDistributionEq extends Serializable
  60. object MonixGramSchmidt
  61. object MonixProverTasks

    A drop-in replacement for FineProverTasks to test the abstract generators approach; since testing is the goal redundancies and some comments have been removed.

  62. object MonixSamples
  63. object MonixTangentFiniteDistribution extends Serializable
  64. object MonixTangentFiniteDistributionEq extends Serializable
  65. object NodeCoeffSeq
  66. object NodeCoeffs
  67. object ParDistEq
  68. object ParGramSchmidt
  69. object ParMapState extends Serializable
  70. object ParStrategicProvers
  71. object ParTangentDistEq
  72. object ParTermState extends Serializable
  73. object PickledTermPopulation extends Serializable
  74. object PostBuffer
  75. object PostData extends Serializable
  76. object PostDiscarder
  77. object PostHistory
  78. object PostMaps
  79. object PostResponse
  80. object Postable
  81. object ProofEntropies extends Serializable
  82. object ProverTasks
  83. object QueryBaseState extends Serializable
  84. object QueryEquations extends Serializable
  85. object QueryFromPosts
  86. object QueryInitState extends Serializable
  87. object QueryOptions extends Serializable
  88. object QueryProver extends Serializable
  89. object Queryable
  90. object RandomVar
  91. object RandomVarFamily
  92. object RandomVarList
  93. object Representation extends Serializable
  94. object RepresentationLearner
  95. object Samples
  96. object SimpleEquations
  97. object Sort
  98. object SortList
  99. object SpireExprEquations
  100. object SpireGradient extends Serializable
  101. object SplitPost extends Serializable
  102. object StateDistribution
  103. object StrategicProvers
  104. object TFData extends Serializable
  105. object TFDist extends Serializable
  106. object TangVec extends Serializable
  107. object TangentFiniteDistribution extends Serializable
  108. object TensorFlowExprEquations
  109. object TermBucket
  110. object TermData
  111. object TermEvolutionStep
  112. object TermEvolver
  113. object TermGenJson
  114. object TermGenParams extends Serializable
  115. object TermGeneratorNodes

    Combining terms and subclasses to get terms, types, functions etc; these are abstract specifications, to be used for generating distributions, obtaining equations etc.

    Combining terms and subclasses to get terms, types, functions etc; these are abstract specifications, to be used for generating distributions, obtaining equations etc. The object contains helpers and other static objects.

  116. object TermNodeCoeffSeq
  117. object TermProver extends CompositeProver[TermResult]
  118. object TermRandomVars
  119. object TermState extends Serializable
  120. object TermsTypThms
  121. object TestCustomQuery
  122. object TruncDistVal extends Serializable
  123. object Truncate
  124. object TruncatedDistribution extends Functor[TruncatedDistribution]
  125. object TruncatedFiniteDistribution extends Serializable
  126. object TypSolver
  127. object TypedPostResponse
  128. object Unify
  129. object WeightVect extends Serializable
  130. object WeightedTermBucket

Deprecated Value Members

  1. object Collections
    Annotations
    @deprecated
    Deprecated

    (Since version 17/5/2017) use spire

  2. object GlobalProver
    Annotations
    @deprecated
    Deprecated

    (Since version now) use composite prover

Ungrouped