Uncertainty in Artificial Intelligence 3 (MACHINE INTELLIGENCE AND PATTERN RECOGNITION)

Being a subject of much controversy in Artificial Intelligence, there are still many open fundamental issues in the area of uncertain reasoning. This third volume presents new research results, representing significant progress in a number of issues. Because representation and reasoning under uncertainty are still poorly understood, and because implementation choices and tradeoffs are best understood in the context of specific applications, most of the papers address multiple issues in uncertain reasoning. They are divided into four categories: Interpretation and comparison of uncertainty calculi; Representation and computation in Bayesian inference; Structure and control for systems reasoning under uncertainty; and Learning and explanation.