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Machine Intelligence 13 ushers in an exciting new phase of artificial intelligence research, one in which machine learning has emerged as a hot-bed of new theory, as a practical tool in engineering disciplines, and as a source of material for cognitive models of the human brain. Based on the Machine Intelligence Workshop of 1992, held at Strathclyde University in Scotland, the book brings together numerous papers from some of the field's leading researchers to discuss current theoretical and practical issues. Highlights include a chapter by J.A. Robinson--the founder of modern computational logic--on the field's great forefathers John von Neumann and Alan Turing, and a chapter by Stephen Muggleton that analyzes Turing's legacy in logic and machine learning. This thirteenth volume in the renowned Machine Intelligence series remains the best source of information for the latest developments in the field. All students and researchers in artificial intelligence and machine learning will want to own a copy.
This volume investigates the intersection of machine learning theory, practical engineering applications, and cognitive modeling within the field of artificial intelligence. The editors, D. Michie, K. Furukawa, and S. Muggleton, compile research presented at the 1992 Machine Intelligence Workshop to establish a framework for understanding the evolution of inductive learning. By synthesizing historical perspectives with contemporary technical papers, the text argues for the continued relevance of computational logic in shaping future machine intelligence research.
What You Will Find
Experts recognize this volume as a significant archival record of early 1990s artificial intelligence research and methodology. Readers frequently note the academic density of the prose, which serves as a foundational reference for students and researchers interested in the historical trajectory of computational logic.
Page Count:
488
Publication Date:
1994-10-13
Publisher:
Clarendon Press
ISBN-10:
0198538502
ISBN-13:
9780198538509
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