The Uncertain Reasoner's Companion
Reasoning under uncertainty, that is, making judgements with only partial knowledge, is a major theme in artificial intelligence. Professor Paris provides here an introduction to the mathematical foundations of the subject. It is suited for readers with some knowledge of undergraduate mathematics but is otherwise self-contained, collecting together the key results on the subject and formalizing within a unified framework the main contemporary approaches and assumptions. The author has concentrated on giving clear mathematical formulations, analyses, justifications and consequences of the main theories about uncertain reasoning, so the book can serve as a textbook for beginners or as a starting point for further basic research into the subject. It will be welcomed by graduate students and research workers in logic, philosophy and computer science as an account of how mathematics and artificial intelligence can complement and enrich each other.
- Applicable to both mathematicans and computer scientists
- Exciting and fashionable area of research at present
Product details
No date availablePaperback
9780521032728
224 pages
228 × 152 × 13 mm
0.361kg
Table of Contents
- Introduction
- 1. Motivation
- 2. Belief as probability
- 3. Justifying belief as probability
- 4. Dempster-Shafer belief
- 5. Truth-functional belief
- 6. Inference processes
- 7. Principles of uncertain reasoning
- 8. Belief revision
- 9. Independence
- 10. Computational feasibility
- 11. Uncertain reasoning in the predicate calculus
- 12. Principles of predicate uncertain reasoning
- Glossary
- Bibliography
- Index.