Hardcover ISBN:  9780821806111 
Product Code:  PSAPM/55 
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eBook ISBN:  9780821892701 
Product Code:  PSAPM/55.E 
List Price:  $125.00 
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Hardcover ISBN:  9780821806111 
eBook: ISBN:  9780821892701 
Product Code:  PSAPM/55.B 
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AMS Member Price:  $203.20 $153.20 
Hardcover ISBN:  9780821806111 
Product Code:  PSAPM/55 
List Price:  $129.00 
MAA Member Price:  $116.10 
AMS Member Price:  $103.20 
eBook ISBN:  9780821892701 
Product Code:  PSAPM/55.E 
List Price:  $125.00 
MAA Member Price:  $112.50 
AMS Member Price:  $100.00 
Hardcover ISBN:  9780821806111 
eBook ISBN:  9780821892701 
Product Code:  PSAPM/55.B 
List Price:  $254.00 $191.50 
MAA Member Price:  $228.60 $172.35 
AMS Member Price:  $203.20 $153.20 

Book DetailsProceedings of Symposia in Applied MathematicsVolume: 55; 1998; 275 ppMSC: Primary 68; Secondary 03; 05; 51; 60; 90;
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.ReadershipGraduate students and research mathematicians interested in artificial intelligence; possibly those interested in philosophy.

Table of Contents

Articles

Frederick Hoffman  Introduction and history [ MR 1619604 ]

Martin Charles Golumbic  Reasoning about time [ MR 1619605 ]

Hélène Kirchner  Orderings in automated theorem proving [ MR 1619606 ]

Catherine Lassez  Programming with constraints: Some aspects of the mathematical foundations [ MR 1619607 ]

Vishvjit S. Nalwa  The basis of computer vision [ MR 1619608 ]

Monty Newborn  Outsearching Kasparov [ MR 1619609 ]

Glenn Shafer  Mathematical foundations for probability and causality [ MR 1619610 ]


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


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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.

Articles

Frederick Hoffman  Introduction and history [ MR 1619604 ]

Martin Charles Golumbic  Reasoning about time [ MR 1619605 ]

Hélène Kirchner  Orderings in automated theorem proving [ MR 1619606 ]

Catherine Lassez  Programming with constraints: Some aspects of the mathematical foundations [ MR 1619607 ]

Vishvjit S. Nalwa  The basis of computer vision [ MR 1619608 ]

Monty Newborn  Outsearching Kasparov [ MR 1619609 ]

Glenn Shafer  Mathematical foundations for probability and causality [ MR 1619610 ]

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