1979-1990

1979-1990

Author: Henryk Sawoniak

Publisher: Walter de Gruyter

Published: 2012-02-14

Total Pages: 1284

ISBN-13: 3110975068

DOWNLOAD EBOOK


Artificial Intelligence in Medicine

Artificial Intelligence in Medicine

Author: David RiaƱo

Publisher: Springer

Published: 2019-06-19

Total Pages: 431

ISBN-13: 303021642X

DOWNLOAD EBOOK

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.


Expert Systems and Related Topics

Expert Systems and Related Topics

Author: Marlene A. Palmer

Publisher: IGI Global

Published: 1990-01-01

Total Pages: 170

ISBN-13: 9781878289032

DOWNLOAD EBOOK

This comprehensive reference to all areas of expert systems and applications, plus advanced related topics, lets you spend your time reading expert systems literature rather than searching for it. It gives you a source of historical perspectives and outlooks on the future of the field. Whether you are a manager, a developer or an end user or researcher, Expert Systems and Related Topics: Selected Bibliography & Guide to Information Sources puts all the sources of expert systems literature at your fingertips.


Compendium of Neurosymbolic Artificial Intelligence

Compendium of Neurosymbolic Artificial Intelligence

Author: P. Hitzler

Publisher: IOS Press

Published: 2023-08-04

Total Pages: 706

ISBN-13: 1643684078

DOWNLOAD EBOOK

If only it were possible to develop automated and trainable neural systems that could justify their behavior in a way that could be interpreted by humans like a symbolic system. The field of Neurosymbolic AI aims to combine two disparate approaches to AI; symbolic reasoning and neural or connectionist approaches such as Deep Learning. The quest to unite these two types of AI has led to the development of many innovative techniques which extend the boundaries of both disciplines. This book, Compendium of Neurosymbolic Artificial Intelligence, presents 30 invited papers which explore various approaches to defining and developing a successful system to combine these two methods. Each strategy has clear advantages and disadvantages, with the aim of most being to find some useful middle ground between the rigid transparency of symbolic systems and the more flexible yet highly opaque neural applications. The papers are organized by theme, with the first four being overviews or surveys of the field. These are followed by papers covering neurosymbolic reasoning; neurosymbolic architectures; various aspects of Deep Learning; and finally two chapters on natural language processing. All papers were reviewed internally before publication. The book is intended to follow and extend the work of the previous book, Neuro-symbolic artificial intelligence: The state of the art (IOS Press; 2021) which laid out the breadth of the field at that time. Neurosymbolic AI is a young field which is still being actively defined and explored, and this book will be of interest to those working in AI research and development.