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# The Institute of Mathematics and Its Applications Conference Series, New: Artificial Intelligence in Mathematics 51 (1994, Hardcover)

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## About this product

### Synopsis

- SynopsisThis book offers a revelatory glimpse into the future--when science, social science, and social administration will be based on the complementary interplay between artificial intelligence, mathematics, and statistics. Comprised of contributions from a broad range of leading scientists and researchers, the book outlines how artificial intelligence supplies insights into the nature of complex problems, mathematics offers a rich language for presenting systems and methods for investigating them rigorously, and statistics provides the interface between theory and data from both observation and experiment. Students and researchers in applied mathematics, artificial intelligence, and statistics interested in the growing integration of computer technologies and modern mathematical breakthroughs will want to read this important new book.

### Product Identifiers

- ISBN-100198536860
- ISBN-139780198536864

### Key Details

- Number Of Pages344 pages
- SeriesThe Institute of Mathematics and Its Applications Conference Series, New
- FormatHardcover
- Publication Date1994-08-25
- LanguageEnglish
- PublisherOxford University Press, Incorporated
- Publication Year1994

### Additional Details

- Series Volume Number51
- Copyright Date1994
- IllustratedYes

### Dimensions

- Weight24.8 Oz
- Height1 In.
- Width6.4 In.
- Length9.5 In.

### Target Audience

- GroupScholarly & Professional

### Classification Method

- LCCN94-020783
- LC Classification NumberQA76.95.A73 1994
- Dewey Decimal510/.285/63
- Dewey Edition20

### Contributors

- Edited byA. D. Vella,J. C. McKee,J. H. Johnson

### Table Of Content

- Table Of ContentPART I: An Introduction to Artificial Intelligence in Mathematics 1. An Introduction to Artificial Intelligence in Mathematics, Jeffrey Johnson, Sean McKee and Alfred Vella PART II: The Impact of Computers on Mathematics: Philosophical and Structural Issues 2. What is Artificial Intelligence and is it Relevant to Mathematics?, James L. Alty 3. Artificial Intelligence and the Mathcycle, Alfred Vella and Carol Vella 4. Learning from AM, Graeme Ritchie 5. Learning Qualitative Models of Dynamic Systems, Ivan Bratko, Stephen Muggleton and Alen Varsek 6. Varieties of Approximations, John S.N. Elvey 7. Uncertainty Versus Computational Complexity, Jean-Claude Simon 8. Representing Ignorance, Or: Knowing What We Do Not Know, Laurent Siklossy PART III: Logic and Computer Proof 9. A System for Multi-Level Mathematical Reasoning, Fausto Giunchiglia and Paolo Traverso 10. From Meta-level Tactics to Object-level Programs, Christian Horn and Alan Smaill 11. Searching Dependency Between Algebraic Equations: An Algorithm Applied to Automated Reasoning, Yang Lu and Zhang Jingzhong PART IV: Artificial Intelligence in Computer Algebra and Computer Systems for Mathematics 12. The Role of Intelligence in Computer Algebra, James H. Davenport 13. An Artificial Intelligence Environment for Computer Algebra, J. Calmet and I.A. Tjandra 14. Modelling Mathematical Objects in Knowledge-Based Systems for Scientific Computing, Francois Rechenmann 15. Hybrid Knowledge Representation and Theorem Proving in Mathematics, Philippe Laublet 16. The Mathematics Understander, Edmund Furse 17. Heuristics for Solving Overdetermined Systems of Partial Differential Equations, Thomas Wolf and Andreas Brand 18. Declarative Programming for Mathematical Exploration, Ron Knott 19. Hypertext for Computational Mathematics, Peter Samuels PART V: Artificial Intelligence in Applied Mathematics and Statistics 20. Artificial Intelligence and Statistics: Synergy in Action?, David J. Hand 21. A Framework for Combining Reasoning Components with Mathematical Software, B. Ford, S.J. Hague, R.M.J. Iles, I. Reid 22. An Intelligent Assistant for the Statistical Analysis of Markov Process Data, Fergus Daly 23. Genetic Algorithms and Optimizing Large Nonlinear Systems, P. Olioveira, S. McKee, C. Coles 24. Representation, Knowledge Elicitation and Mathematical Science, Jeffrey Johnson

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