Machine Learning, Meta-Reasoning and Logics

Name: Machine Learning, Meta-Reasoning and Logics
Brand: Springer-Verlag New York Inc.
SKU: 9781461289067
Price: 149.88 EUR
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Autor: Pavel B. Brazdil, Kurt Konolige

Jazyk:

Väzba: Brožovaná

Vydavateľ: Springer-Verlag New York Inc.

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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 - Brožovaná

Vydalo

2011

Stránok

328

EAN

9781461289067

ISBN

1461289068

Enbook ID

02179877

Vydavateľ

Springer-Verlag New York Inc.

Hmotnosť

669

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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