This book explores why, regarding practical reasoning, humans are sometimes still faster than artificial intelligence systems. It is the first to offer a self-contained presentation of neural network models for many computer science logics.
The new edition of this extraordinary book depicts the creation of the world champion checkers computer program, Chinook. Written by the originator and leader of the Chinook team, it also reveals the human factor behind the program’s design.
This book presents the NeOn Methodology Framework, which includes nine scenarios for collaboratively building ontologies and ontology networks. It provides the reader with a description of the key activities relevant to the ontology engineering life-cycle.
The first book dedicated to this new branch of machine learning and data mining, this comprehensive treatment, which covers everything from label ranking to preference learning and recommender systems, will be required reading for researchers working in AI.
This comprehensive book describes Probabilistic Logic Networks (PLN), a novel conceptual, mathematical and computational approach to uncertain inference. A broad scope of reasoning types are considered.
Reinforcement learning has evolved to tackle domains that are yet to be fully understood, or are too complex for a closed description. In this book the author investigates whether suitable abstraction methods can overcome the discipline’s deficiencies.
This book presents an introduction, both non-technical and technical, to modern quantum neural computation. It combines quantum computation with neural computation and provides a blueprint for the future quantum brain.