Ebook: Readings in Uncertain Reasoning

Morgan Kaufmann Series in Representation and Reasoning
Ronad J. Brachmann, Series Editor
"Readings in Uncertain Reasoning"
Edited by Glenn Shafer, University of Kansas
and Judea Pearl, University of California, Los Angeles
with a contribution by Paul R. Cohen, University of Massachusetts, Amherst

Most everyday reasoning and decision making is based on uncertain premises.

Human actions are based on guesses, often requiring explicit weighting of conflicting stimuli and evidence.

The readings in this book address the methods that have been used in artificial intelligence to build systems with the ability to manage uncertainty.

An authoritative and thorough colleciton of work, this volume presents forty-two key papers from the literature. In addition, the editors have provided introductions to the volume and to groups of papers that offer informative commentary and unifying perspective. In selecting the readings for the volume, the editors have represented all of the major approaches to work in the field and have related them to the historical tradition of probabilistic methods.

This volume will be useful as a text or supplement for courses in artificial intelligence with an emphasis on expert systems and commonsense reasoning. It will also be valuable reference for researchers, system developers and students in computer science, statistics, operations research, engineering, cognitive science and many other fields.