Systems that learn : an introduction to learning theory /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Jain, Sanjay, 1965 February 22-
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge, Mass. : MIT Press, ©1999.
©1999
Edición:2nd ed.
Colección:Learning, development, and conceptual change.
Temas:
Learning > Mathematical aspects.
Learning, Psychology of.
Human information processing > Mathematical models.
Psychologie de l'apprentissage.
Traitement de l'information chez l'être humain > Modèles mathématiques.
SCIENCE > Cognitive Science.
PSYCHOLOGY > Cognitive Psychology.
Human information processing > Mathematical models
Learning, Psychology of
Leertheorieën.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Empirical inquiry
  • Paradigms
  • Some simple paradigms
  • Formalities
  • Identification
  • Languages as theoretically possible realities
  • Language identification: Hypotheses, data
  • Language identification: Scientists
  • Language identification: Scientific success
  • Identification as a limiting process
  • Characterization of identifiable
  • Some alternative paradigms
  • Memory-limited scientists
  • Second paradigm: Identification of functions
  • Characterization of identifiable
  • Exercises
  • Identification by Computable Scientists
  • Language identification by computable scientist
  • Function identification by computable scientist
  • Parameterized scientists
  • Exact identification
  • Fundamental Paradigms Generalized
  • Strategies for Learning
  • Strategies for language identification: Introduction
  • Constraints on potential conjectures
  • Constraints on the use of information
  • Constraint on convergence
  • Constraints on the relation between conjectures
  • Strategies for function identification
  • Criteria of Learning
  • Criteria for function identification
  • Criteria of language identification
  • Inference of Approximations
  • Approximations
  • Approximate explanatory identification
  • Uniform approximate explanatory identification
  • Environments
  • Inaccurate data
  • Texts with additional structure
  • Multiple texts
  • Part III: Additional Topics
  • Team and Probabilistic Learning
  • Motivation for identification by teams
  • Team identification of functions
  • Identification by probabilistic scientists.

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