Artificial Intelligence Frontiers in Statistics: Al and Statistics III

by Hand; David J.

• ISBN13: 9780412407109
• ISBN10: 0412407108
• Format: Hardcover
• Copyright: 1992-12-01
• Publisher: Chapman & Hall/

Summary

This book presents a summary of recent work on the interface between artificial intelligence and statistics. It does this through a series of papers by different authors working in different areas of this interface. These papers are a selected and referenced subset of papers presented at the 3rd Interntional Workshop on Artificial Intelligence and Statistics, Florida, January 1991.

Table of Contents

List of contributors
Introduction
Statistical expert systems	p. 1
DEXPERT: an expert system for the design of experiments	p. 3
Inside two commercially available statistical expert systems	p. 17
AMIA: Aide a la Modelisation par l'Intelligence Artificielle (expert system for simulation modelling and sectoral forecasting)	p. 31
An architecture for knowledge-based statistical support systems	p. 39
Enhancing explanation capabilities of statistical expert systems through hypertext	p. 46
Measurement scales as metadata	p. 54
Belief networks	p. 65
On the design of belief networks for knowledge-based systems	p. 67
Lack-of-information based control in graphical belief systems	p. 82
Adaptive importance sampling for Bayesian networks applied to filtering problems	p. 90
Intelligent arc addition, belief propagation and utilization of parallel processors by probabilistic inference engines	p. 106
A new method for representing and solving Bayesian decision problems	p. 109
Learning	p. 139
Inferring causal structure in mixed populations	p. 141
A knowledge acquisition inductive system guided by empirical interpretation of derived results	p. 156
Incorporating statistical techniques into empirical symbolic learning systems	p. 168
Learning classification trees	p. 182
An analysis of two probabilistic model induction techniques	p. 202
Neural networks	p. 215
A robust back propagation algorithm for function approximation	p. 217
Maximum likelihood training of neural networks	p. 241
A connectionist knowledge acquisition tool: CONKAT	p. 256
Connectionist, rule-based, and Bayesian decision aids: an empirical comparison	p. 264
Text manipulation	p. 279
Statistical approaches to aligning sentences and identifying word correspondences in parallel texts: a report on work in progress	p. 281
Probabilistic text understanding	p. 295
The application of machine learning techniques in subject classification	p. 312
Other areas	p. 325
A statistical semantics for causation	p. 327
Admissible stochastic complexity models for classification problems	p. 335
Combining the probability judgements of experts: statistical and artificial intelligence approaches	p. 348
Randomness and independence in non-monotonic reasoning	p. 362
Consistent regions in probabilistic logic when using different norms	p. 370
A decision theoretic approach to controlling the cost of planning	p. 387
Index	p. 401
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