Machine Learning, Meta-Reasoning and Logics

Name: Machine Learning, Meta-Reasoning and Logics
Brand: Springer
SKU: 9780792390473
Price: 162.38 EUR
Availability: InStock

Autor: Pavel B. Brazdil, Kurt Konolige

Jazyk:

Väzba: Pevná

Vydavateľ: Springer

Dostupnosť: Skladom u dodávateľa v malom množstve

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162.38 €

This book contains a selection of papers presented at the International Workshop Machine Learning, M...

Informácie o knihe

Autor

Pavel B. Brazdil, Kurt Konolige

Jazyk

Angličtina

Väzba

Kniha - Pevná

Stránok

328

EAN

9780792390473

ISBN

0792390474

Enbook ID

01397980

Vydavateľ

Springer

Hmotnosť

1820

Rozmery

178 x 254 x 20

Kompletný popis

This book contains a selection of papers presented at the International Workshop Machine Learning, Meta-Reasoning and Logics held in Hotel de Mar in Sesimbra, Portugal, 15-17 February 1988. All the papers were edited afterwards. The Workshop encompassed several fields of Artificial Intelligence: Machine Learning, Belief Revision, Meta-Reasoning and Logics. The objective of this Workshop was not only to address the common issues in these areas, but also to examine how to elaborate cognitive architectures for systems capable of learning from experience, revising their beliefs and reasoning about what they know. Acknowledgements The editing of this book has been supported by COST-13 Project Machine Learning and Knowledge Acquisition funded by the Commission o/the European Communities which has covered a substantial part of the costs. Other sponsors who have supported this work were Junta Nacional de lnvestiga~ao Cientlfica (JNICT), lnstituto Nacional de lnvestiga~ao Cientlfica (INIC), Funda~ao Calouste Gulbenkian. I wish to express my gratitude to all these institutions. Finally my special thanks to Paula Pereira and AnaN ogueira for their help in preparing this volume. This work included retyping all the texts and preparing the camera-ready copy. Introduction 1 1. Meta-Reasoning and Machine Learning The first chapter is concerned with the role meta-reasoning plays in intelligent systems capable of learning. As we can see from the papers that appear in this chapter, there are basically two different schools of thought.

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