New Titles  |  FAQ  |  Keep Informed  |  Review Cart  |  Contact Us Quick Search (Advanced Search ) Browse by Subject General Interest Logic & Foundations Number Theory Algebra & Algebraic Geometry Discrete Math & Combinatorics Analysis Differential Equations Geometry & Topology Probability & Statistics Applications Mathematical Physics Math Education
Mathematical Aspects of Artificial Intelligence
Edited by: Frederick Hoffman, Florida Atlantic University, Boca Raton
 SEARCH THIS BOOK:
Proceedings of Symposia in Applied Mathematics
1998; 275 pp; hardcover
Volume: 55
ISBN-10: 0-8218-0611-4
ISBN-13: 978-0-8218-0611-1
List Price: US$60 Member Price: US$48
Order Code: PSAPM/55

There exists a history of great expectations and large investments involving Artificial Intelligence (AI). There are also notable shortfalls and memorable disappointments. One major controversy regarding AI is just how mathematical a field it is or should be.

This text includes contributions that examine the connections between AI and mathematics, demonstrating the potential for mathematical applications and exposing some of the more mathematical areas within AI. The goal is to stimulate interest in people who can contribute to the field or use its results.

Included is work by M. Newborn on the famous Deep Blue chess match. He discusses highly mathematical techniques involving graph theory, combinatorics and probability and statistics. G. Shafer offers his development of probability through probability trees with some of the results appearing here for the first time. M. Golumbic treats temporal reasoning with ties to the famous Frame Problem. His contribution involves logic, combinatorics and graph theory and leads to two chapters with logical themes. H. Kirchner explains how ordering techniques in automated reasoning systems make deduction more efficient. Constraint logic programming is discussed by C. Lassez, who shows its intimate ties to linear programming with crucial theorems going back to Fourier. V. Nalwa's work provides a brief tour of computer vision, tying it to mathematics--from combinatorics, probability and geometry to partial differential equations.

All authors are gifted expositors and are current contributors to the field. The wide scope of the volume includes research problems, research tools and good motivational material for teaching.

Graduate students and research mathematicians interested in artificial intelligence; possibly those interested in philosophy.

Reviews

"Although this book was written to introduce mathematicians to AI, the book is also likely to be a valuable resource for cognitive scientists and mathematical psychologists."

-- Journal of Mathematical Psychology

"Seven excellent papers are included, covering important AI topics."

-- Mathematical Reviews

• F. Hoffman -- Introduction and history
• M. C. Golumbic -- Reasoning about time
• H. Kirchner -- Orderings in automated theorem proving
• C. Lassez -- Programming with constraints: Some aspects of the mathematical foundations
• V. Nalwa -- The basis of computer vision
• M. Newborn -- Outsearching Kasparov
• G. Shafer -- Mathematical foundations for probability and causality
• Index