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.
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 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 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 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.
This text covers a field of research involving the use of neural network techniques for image recognition to tasks in the area of micromechanics. It includes theoretical analysis, details of machine tool prototypes, and results from various experiments.
This book covers the theory and practice of multiparadigm constraint programming languages. It details the merging of programming concepts which yields multiparadigm (constraint) programming languages and examines two concrete approaches.