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A Geometric Approach to the Unification of Symbolic Structures and Neural Networks (Hardcover, 1st ed. 2021): Tiansi Dong A Geometric Approach to the Unification of Symbolic Structures and Neural Networks (Hardcover, 1st ed. 2021)
Tiansi Dong
R3,611 Discovery Miles 36 110 Ships in 10 - 15 working days

The unification of symbolist and connectionist models is a major trend in AI. The key is to keep the symbolic semantics unchanged. Unfortunately, present embedding approaches cannot. The approach in this book makes the unification possible. It is indeed a new and promising approach in AI. -Bo Zhang, Director of AI Institute, Tsinghua It is indeed wonderful to see the reviving of the important theme Nural Symbolic Model. Given the popularity and prevalence of deep learning, symbolic processing is often neglected or downplayed. This book confronts this old issue head on, with a historical look, incorporating recent advances and new perspectives, thus leading to promising new methods and approaches. -Ron Sun (RPI), on Governing Board of Cognitive Science Society Both for language and humor, approaches like those described in this book are the way to snickerdoodle wombats. -Christian F. Hempelmann (Texas A&M-Commerce) on Executive Board of International Society for Humor Studies

A Geometric Approach to the Unification of Symbolic Structures and Neural Networks (Paperback, 1st ed. 2021): Tiansi Dong A Geometric Approach to the Unification of Symbolic Structures and Neural Networks (Paperback, 1st ed. 2021)
Tiansi Dong
R3,574 Discovery Miles 35 740 Ships in 10 - 15 working days

The unification of symbolist and connectionist models is a major trend in AI. The key is to keep the symbolic semantics unchanged. Unfortunately, present embedding approaches cannot. The approach in this book makes the unification possible. It is indeed a new and promising approach in AI. -Bo Zhang, Director of AI Institute, Tsinghua It is indeed wonderful to see the reviving of the important theme Nural Symbolic Model. Given the popularity and prevalence of deep learning, symbolic processing is often neglected or downplayed. This book confronts this old issue head on, with a historical look, incorporating recent advances and new perspectives, thus leading to promising new methods and approaches. -Ron Sun (RPI), on Governing Board of Cognitive Science Society Both for language and humor, approaches like those described in this book are the way to snickerdoodle wombats. -Christian F. Hempelmann (Texas A&M-Commerce) on Executive Board of International Society for Humor Studies

Recognizing Variable Environments - The Theory of Cognitive Prism (Paperback, 2012): Tiansi Dong Recognizing Variable Environments - The Theory of Cognitive Prism (Paperback, 2012)
Tiansi Dong
R2,830 Discovery Miles 28 300 Ships in 10 - 15 working days

Normal adults do not have any difficulty in recognizing their homes. But can artificial systems do in the same way as humans? This book collects interdisciplinary evidences and presents an answer from the perspective of computing, namely, the theory of cognitive prism. To recognize an environment, an intelligent system only needs to classify objects, structures them based on the connection relation (not through measuring!), subjectively orders the objects, and compares with the target environment, whose knowledge is similarly structured. The intelligent system works, therefore, like a prism: when a beam of light (a scene) reaches (is perceived) to an optical prism (by an intelligent system), some light (objects) is reflected (are neglected), those passed through (the recognized objects) are distorted (are ordered differently). So comes the term 'cognitive prism'! Two fundamental propositions used in the theory can be informally stated as follow: an orientation relation is a kind of distance comparison relation -- you being in front of me means you being nearer to my face than to my other sides; a pair of objects being connected means any object, precisely the space occupied by the object, can be moved to a place where it connects with the pair.

Recognizing Variable Environments - The Theory of Cognitive Prism (Hardcover, 2012 ed.): Tiansi Dong Recognizing Variable Environments - The Theory of Cognitive Prism (Hardcover, 2012 ed.)
Tiansi Dong
R2,866 Discovery Miles 28 660 Ships in 10 - 15 working days

Normal adults do not have any difficulty in recognizing their homes. But can artificial systems do in the same way as humans? This book collects interdisciplinary evidences and presents an answer from the perspective of computing, namely, the theory of cognitive prism. To recognize an environment, an intelligent system only needs to classify objects, structures them based on the connection relation (not through measuring!), subjectively orders the objects, and compares with the target environment, whose knowledge is similarly structured. The intelligent system works, therefore, like a prism: when a beam of light (a scene) reaches (is perceived) to an optical prism (by an intelligent system), some light (objects) is reflected (are neglected), those passed through (the recognized objects) are distorted (are ordered differently). So comes the term 'cognitive prism'! Two fundamental propositions used in the theory can be informally stated as follow: an orientation relation is a kind of distance comparison relation -- you being in front of me means you being nearer to my face than to my other sides; a pair of objects being connected means any object, precisely the space occupied by the object, can be moved to a place where it connects with the pair.

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