Traditional Learning Theories, Process Philosophy and AI - Grand Format

Edition en anglais

Note moyenne 
Vesselin Petrov et Katie Anderson - Traditional Learning Theories, Process Philosophy and AI.
This book provides such a basis with the help of Whitehead's cyclic learning theory and its process ontology, making it possible to integrate the dominant... Lire la suite
24,00 € Neuf
Actuellement indisponible

Résumé

This book provides such a basis with the help of Whitehead's cyclic learning theory and its process ontology, making it possible to integrate the dominant learning theories of our time. It is the outcome of a project sponsored by the Bulgarian National Science Fund. Dr Vesselin Petrov holds an M. A. in mathematics (1977), a Ph. D. in philosophy (1989) and a D. Sc. in philosophy (2011). He is a Professor and the Director of the Institute for the Study of Societies and Knowledge at the Bulgarian Academy of Sciences.
His fields of research include process-relational philosophy, metaphysics, ontology, applied ontology, philosophy of mathematics, and philosophy of education. He leads the team of the project "Synergy between process philosophy and elements of AI in the theory of learning" sponsored by the Bulgarian National Science Fund". Dr Katie Anderson holds a B. A. in philosophy (2010) from the University of Cambridge and a PhD in psychology (2017) from London Southbank University.
Her PhD draws on Whitehead's process-relational metaphysics and has given rise to two publications. She is currently a researcher in the field of mental health, working at St George's University.

Caractéristiques

  • Date de parution
    14/05/2019
  • Editeur
  • Collection
  • ISBN
    978-2-930517-60-5
  • EAN
    9782930517605
  • Format
    Grand Format
  • Présentation
    Broché
  • Nb. de pages
    222 pages
  • Poids
    0.36 Kg
  • Dimensions
    16,0 cm × 24,0 cm × 0,0 cm

Avis libraires et clients

Avis audio

Écoutez ce qu'en disent nos libraires !

L'éditeur en parle

Artificial intelligence research connected with learning theory ("deep learning, " "machine learning, " analysis of the quality of learning, etc.) has existed for many years ; however, there have been few investigations in that area conducted from a robust philosophical methodological basis.

Des mêmes auteurs

Les clients ont également aimé

Derniers produits consultés