Traditional Learning Theories, Process Philosophy and AI

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. Lees verder

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.


Paperback - In het Engels 24,00 €
PDF - In het Engels 16,00 €

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Gegevens


Uitgever
Les Politiques sociales
Imprint
Presses universitaires de Louvain
Auteur
Katie Anderson, Vesselin Petrov,
Collectie
Phylopraxis
Taal
français
BISAC Subject Heading
PHI000000 PHILOSOPHY
Onix Audience Codes
06 Professional and scholarly
CLIL (2013)
3080 SCIENCES HUMAINES ET SOCIALES, LETTRES
Voor het eerst gepubliceerd
14 mei 2019
Oorspronkelijke taal
English

Paperback


Product Detail
1
Publicatie datum
29 november 2018
ISBN-13
9782875510891
Omvang
Aantal pagina's hoofdinhoud : 280
Code
9782875510891
Formaat
21,2 x 29,7 cm
Gewicht
725 grams
Aanbevolen verkoopprijs
28,00 €
ONIX XML
Version 2.1, Version 3

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