Table of Contents
Chapter 1: UNCERTAINTY IN AI SYSTEMS: AN OVERVIEW
1.2 EXTENSIONAL SYSTEMS: MERITS, DEFICIENCIES, AND REMEDIES
1.3 INTENSIONAL SYSTEMS AND NETWORK REPRESENTATIONS
1.4 THE CASE FOR PROBABILITIES
1.5 QUALITATIVE REASONING WITH PROBABILITIES
2.3 EPISTEMOLOGICAL ISSUES OF BELIEF UPDATING
2.4 BIBLIOGRAPHICAL AND HISTORICAL REMARKS
Chapter 3: MARKOV AND BAYESIAN NETWORKS: Two Graphical Representations of Probabilistic Knowledge
Get Probabilistic Reasoning in Intelligent Systems now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.