Machine learning : proceedings of the ninth international workshop (ML92)

Content: 
Front Matter, Page i
Copyright, Page ii
Preface, Page vii, Derek Sleeman, Peter Edwards
Program Committee, Page viii
ML 92 Informal Workshop Themes and Coordinators, Page viii
Generalizing from Case Studies: A Case Study, Pages 1-10, David W. Aha
On Learning More Concepts, Pages 11-19, Hussein Almuallim, Thomas G. Dietterich
The Principal Axes Method for Constructive Induction, Pages 20-29, Jerzy W. Bala, Ryszard S. Michalski, Janusz Wnek
Learning by Incomplete Explanations of Failures in Recursive Domains, Pages 30-36, Neeraj Bhatnagar
Eliminating Redundancy in Explanation-Based Learning, Pages 37-42, Henrik Boström
Trading off Consistency and Efficiency in Version-Space Induction, Pages 43-48, Claudio Carpineto
Peepholing: choosing attributes efficiently for megainduction, Pages 49-54, J. Catlett
Improving Path Planning with Learning, Pages 55-61, Pang C. Chen
THE RIGHT REPRESENTATION FOR DISCOVERY: FINDING THE CONSERVATION OF MOMENTUM, Pages 62-71, Peter C-H. Cheng, Herbert A. Simon
Learning to Predict in Uncertain Continuous Tasks, Pages 72-81, Alan D. Christiansen
Lazy Partial Evaluation: An Integration of Explanation-Based Generalisation and Partial Evaluation, Pages 82-91, Peter Clark, Rob Holte
A Teaching Method for Reinforcement Learning, Pages 92-101, Jeffery A. Clouse, Paul E. Utgoff
Compiling Prior Knowledge Into an Explicit Bias, Pages 102-110, William W. Cohen
Spatial analogy and subsumption, Pages 111-116, Darrell Conklin, Janice Glasgow
Learning to Satisfy Conjunctive Goals, Pages 117-122, Timothy M. Converse, Kristian J. Hammond
Multistrategy Learning with Introspective Meta-Explanations, Pages 123-128, Michael T. Cox, Ashwin Ram
An Asymptotic Analysis of Speedup Learning, Pages 129-136, Oren Etzioni
Why EBL Produces Overly-Specific Knowledge: A Critique of the PRODIGY Approaches, Pages 137-143, Oren Etzioni, Steven Minton
Automatic Feature Generation for Problem Solving Systems, Pages 144-153, Tom E. Fawcett, Paul E. Utgoff
Towards Inductive Generalisation in Higher Order Logic, Pages 154-162, Cao Feng, Stephen Muggleton
Ordering Effects in Clustering, Pages 163-168, Douglas Fisher, Ling Xu, Nazih Zard
Learning Structured Concepts Using Genetic Algorithms, Pages 169-178, Attilio Giordana, Claudio Sale
An Analysis of Learning to Plan as a Search Problem, Pages 179-188, Jonathan Gratch, Gerald DeJong
An Approach to Anytime Learning, Pages 189-195, John J. Grefenstette, Connie Loggia Ramsey
Artificial Universes - Towards a Systematic Approach to Evaluating Algorithms which Learn from Examples, Pages 196-205, Ray J. Hickey
Average Case Analysis of Learning k-CNF Concepts, Pages 206-211, Daniel S. Hirschberg, Michael J. Pazzani
The MENTLE Approach to Learning Heuristics for the Control of Logic Programs, Pages 212-217, Elizabeth I. Hogger, Krysia Broda
Fuzzy Substructure Discovery, Pages 218-223, Lawrence B. Holder, Diane J. Cook, Horst Bunke
Efficient Classification of Massive, Unsegmented Datastreams, Pages 224-232, Lawrence Hunter, Nomi Harris, David J. States
Induction of One-Level Decision Trees, Pages 233-240, Wayne Iba, Pat Langley
Combining Competition and Cooperation in Supervised Inductive Learning, Pages 241-248, Cezary Z. Janikow
A Practical Approach to Feature Selection, Pages 249-256, Kenji Kira, Larry A. Rendell
Learning as Optimization: Stochastic Generation of Multiple Knowledge, Pages 257-262, Igor Kononenko, Matevž Kovačič
Dynamic Optimization, Pages 263-272, Philip Laird
Sub-unification: A Tool for Efficient Induction of Recursive Programs, Pages 273-281, Stéphane Lapointe, Stan Matwin
Augmenting and Efficiently Utilizing Domain Theory in Explanation-Based Natural Language Acquisition, Pages 282-289, Rey-Long Liu, Von-Wun Soo
Enhancing Transfer in Reinforcement Learning by Building Stochastic Models of Robot Actions, Pages 290-299, Sridhar Mahadevan
THOUGHT: An Integrated Learning System for Acquiring Knowledge Structure, Pages 300-309, Chengjiang Mao
An Approach to Concept Learning Based on Term Generalization, Pages 310-315, Zdravko Markov
Using Transitional Proximity for Faster Reinforcement Learning, Pages 316-321, R. Andrew McCallum
NFDT: A System that Learns Flexible Concepts based on Decision Trees for Numerical Attributes, Pages 322-331, Thierry Van de Merckt
A symbolic algorithm for computing coefficients' accuracy in regression, Pages 332-337, Marjorie Moulet
Compression, Significance and Accuracy, Pages 338-347, Stephen Muggleton, Ashwin Srinivasan, Michael Bain
Guiding Example Acquisition by Generating Scenarios, Pages 348-354, Yves Niquil
Constructive Induction Using a Non-Greedy Strategy for Feature Selection, Pages 355-360, Arlindo L. Oliveira, Alberto Sangiovanni-Vincentelli
Training Second-Order Recurrent Neural Networks using Hints, Pages 361-366, Christian W. Omlin, C. Lee Giles
DYNAMIC: A new role for training problems in EBL, Pages 367-372, M. Alicia Pérez, Oren Etzioni
A Framework for Discovering Discrete Event Models, Pages 373-378, Ashvin Radiya, Jan M. Żytkow
Learning Episodes for Optimization, Pages 379-384, David Ruby, Dennis Kibler
Learning to Fly, Pages 385-393, Claude Sammut, Scott Hurst, Dana Kedzier, Donald Michie
Deconstructing the Digit Recognition Problem, Pages 394-399, Cullen Schaffer
On Combining Multiple Speedup Techniques, Pages 400-405, Alberto Maria Segre
Scaling Reinforcement Learning Algorithms by Learning Variable Temporal Resolution Models, Pages 406-415, Satinder P. Singh
Detecting Novel Classes with Applications to Fault Diagnosis, Pages 416-425, Padhraic Smyth, Jeff Mellstrom
Measuring Utility and the Design of Provably Good EBL Algorithms, Pages 426-435, Devika Subramanian, Scott Hunter
Refining a Relational Theory with Multiple Faults in the Concept and Subconcepts, Pages 436-444, Somkiat Tangkitvanich, Masamichi Shimura
Cooperation in Knowledge Base Refinement, Pages 445-450, Gheorghe D. Tecuci
Temporal Difference Learning of Backgammon Strategy, Pages 451-457, Gerald Tesauro
AGIL : solving the Exploration versus Exploitation dilemma in a simple classifier system applied to simulated robotics, Pages 458-463, Gilles Venturini
Conceptual Clustering with Systematic Missing Values, Pages 464-469, Jerry B. Weinberg, Gautam Biswas, Glenn R. Koller
Selecting Typical Instances in Instance-Based Learning, Pages 470-479, Jianping Zhang
The first phase of real-world discovery: determining repeatability and error of experiments, Pages 480-485, Jan M. Żytkow, Jieming Zhu, Robert Zembowicz
Author Index, Page 486
Subject Index, Pages 487-488