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Artificial Intelligence Frontiers in Statistics : Al and Statistics III - David J. Hand

Artificial Intelligence Frontiers in Statistics

Al and Statistics III

Hardcover

Published: 1st December 1992
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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.

"This is an interesting collection of specialised papers in a new field. Good AI libraries and all research groups will need a copy." -Computing "The book provides a broad update of current work tat should aid researchers on both sides of the AI/Statistics interface, and is a useful successor to earlier volumes in the series from W A Gale." -Short Book Reviews ..."the book is a substantial and worthwhile contribution to the literature for both AI and Statistics. It collects a lot of major results from the frontiers of both sciences and presents them in a very readable context...I enjoyed reading this book very much." -Engineering Applications in Artificial Intelligence

List of contributors
Introduction
Statistical expert systemsp. 1
DEXPERT: an expert system for the design of experimentsp. 3
Inside two commercially available statistical expert systemsp. 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 systemsp. 39
Enhancing explanation capabilities of statistical expert systems through hypertextp. 46
Measurement scales as metadatap. 54
Belief networksp. 65
On the design of belief networks for knowledge-based systemsp. 67
Lack-of-information based control in graphical belief systemsp. 82
Adaptive importance sampling for Bayesian networks applied to filtering problemsp. 90
Intelligent arc addition, belief propagation and utilization of parallel processors by probabilistic inference enginesp. 106
A new method for representing and solving Bayesian decision problemsp. 109
Learningp. 139
Inferring causal structure in mixed populationsp. 141
A knowledge acquisition inductive system guided by empirical interpretation of derived resultsp. 156
Incorporating statistical techniques into empirical symbolic learning systemsp. 168
Learning classification treesp. 182
An analysis of two probabilistic model induction techniquesp. 202
Neural networksp. 215
A robust back propagation algorithm for function approximationp. 217
Maximum likelihood training of neural networksp. 241
A connectionist knowledge acquisition tool: CONKATp. 256
Connectionist, rule-based, and Bayesian decision aids: an empirical comparisonp. 264
Text manipulationp. 279
Statistical approaches to aligning sentences and identifying word correspondences in parallel texts: a report on work in progressp. 281
Probabilistic text understandingp. 295
The application of machine learning techniques in subject classificationp. 312
Other areasp. 325
A statistical semantics for causationp. 327
Admissible stochastic complexity models for classification problemsp. 335
Combining the probability judgements of experts: statistical and artificial intelligence approachesp. 348
Randomness and independence in non-monotonic reasoningp. 362
Consistent regions in probabilistic logic when using different normsp. 370
A decision theoretic approach to controlling the cost of planningp. 387
Indexp. 401
Table of Contents provided by Blackwell. All Rights Reserved.

ISBN: 9780412407109
ISBN-10: 0412407108
Audience: Tertiary; University or College
Format: Hardcover
Language: English
Number Of Pages: 432
Published: 1st December 1992
Publisher: CHAPMAN & HALL
Country of Publication: US
Dimensions (cm): 23.93 x 16.41  x 2.62
Weight (kg): 0.69
Edition Number: 1