Table of Contents
List of contributors Introduction D.J. Hand — PART ONE Statistical expert systems — 1 DEXPERT: an expert system for the design of experiments /T.J. Lorenzen, L.T. Truss, W.S. Spangler, W.T. Corpus and A.B. Parker — 2 Inside two commercially available statistical expert systems /J.F.M. Raes — 3 AMIA: Aide a la Modelisation par l'lntelligence Artificielle (expert system for simulation modelling and sectoral forecasting) /M. Ollivier, R. Arrus, JML-A. Durillon, S. Robert and B. Debord — 4 An architecture for knowledge-based statistical support systems /A. Prat, E. Edmonds, J.M. Catot, J. Lores, J. Galmes and P. Fletcher — 5 Enhancing explanation capabilities of statistical expert systems through hypertext /P. Hietala — 6 Measurement scales as metadata D.J. Hand PART TWO Belief networks — 7 On the design of belief networks for knowledge-based systems /B. Abramson — 8 Lack-of-information based control in graphical belief systems — 9 Adaptive importance sampling for Bayesian networks applied to filtering problems /A.R. Runnalls — 10 Intelligent arc addition, belief propagation and utilization of parallel processors by probabilistic inference engines /A. Ranjbar and M. McLeish — 11 A new method for representing and solving Bayesian decision problems /P.P. Shenoy — PART THREE Learning — 12 Inferring causal structure in mixed populations /C. Glymour, P. Spirtes and R. Scheines — 13 A knowledge acquisition inductive system guided by empirical interpretation of derived results /K. Tsujino and S. Nishida — 14 Incorporating statistical techniques into empirical symbolic learning systems /F. Esposito, D. Malerba and G. Semeraro — 15 Learning classification trees /W. Buntine — 16 An analysis of two probabilistic model induction techniques /S.L. Crawford and M. Fung — PART FOUR Neural networks — 17 A robust back propagation algorithm for function approximation /D.S. Chen and R.C. Jain — 18 Maximum likelihood training of neural networks /H. Gish — 19 A connectionist knowledge acquisition tool: CONKAT /A. Ultsch, R. Mantyk and G. Halmans — 20 Connectionist, rule-based, and Bayesian decision aids: an empirical comparison /S. Schwartz, J. Wiles, I. Gough and S. Phillips — PART FIVE Text manipulation — 21 Statistical approaches to aligning sentences and identifying word correspondences in parallel texts: a report on work in progress /W.A. Gale and K.W. Church — 22 Probabilistic text understanding /R.P. Goldman and E. Charniak — 23 The application of machine learning techniques in subject classification /I. Kavanagh, C. Ward and J. Dunnion — PART SIX Other areas — 24 A statistical semantics for causation /J. Pearl and T.S. Verma — 25 Admissible stochastic complexity models for classification problems /P. Smyth — 26 Combining the probability judgements of experts: statistical and artificial intelligence approaches /LA. Cox — 27 Randomness and independence in non-monotonic reasoning /E. Neufeld — 28 Consistent regions in probabilistic logic when using different norms /D. Bouchaffra — 29 A decision theoretic approach to controlling the cost of planning /L. Hartman — Index.
