000			02486cam a2200289zu 4500
001			88973873
003			FRCYB88973873
005			20251020124245.0
006			m o d
007			cr un
008			251020s2023 fr | o|||||0|0|||eng d
020			_a9781643684062
035			_aFRCYB88973873
040			_aFR-PaCSA _ben _c _erda
100	1		_aSarker, Md Kamruzzaman
245	0	1	_aCompendium of Neurosymbolic Artificial Intelligence _c['Sarker, Md Kamruzzaman', 'Eberhart, Aaron']
264		1	_bSAGE Publications _c2023
300			_a p.
336			_btxt _2rdacontent
337			_bc _2rdamdedia
338			_bc _2rdacarrier
650		0	_a
700	0		_aSarker, Md Kamruzzaman
700	0		_aEberhart, Aaron
856	4	0	_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88973873 _qtext/html _a
520			_aIf 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.
999			_c1556792 _d1556792