ICML 1988

49 papers

A Hill-Climbing Approach to Machine Discovery Donald Rose, Pat Langley

A Knowledge Intensive Approach to Concept Induction Francesco Bergadano, Attilio Giordana

Active Explanation Reduction: An Approach to the Multiple Explanations Problem Shankar A. Rajamoney, Gerald DeJong

An Approach Based on Integrated Learning to Generating Stories Claudio Carpineto

An Empirical Comparison of Genetic and Decision-Tree Classifiers J. Ross Quinlan

AutoClass: A Bayesian Classification System Peter C. Cheeseman, James Kelly, Matthew Self, John C. Stutz, Will Taylor, Don Freeman

Boundaries of Operationality Michael S. Braverman, Stuart J. Russell

Building and Using Mental Models in a Sensory-Motor Domain Bartlett W. Mel

Classifier Systems with Hamming Weights Lawrence Davis, David K. Young

Competitive Reinforcement Learning Kenton J. Lynne

Concept Simplification and Prediction Accuracy Douglas H. Fisher, Jeffrey C. Schlimmer

Conceptual Clumping of Binary Vectors with Occam's Razor Jakub Segen

Connectionist Learning of Expert Backgammon Evaluations Gerald Tesauro

Deferred Commitment in UNIMEM: Waiting to Learn Michael Lebowitz

Diffy-S: Learning Robot Operator Schemata from Examples Carl Myers Kadie

Experimental Results from an Evaluation of Algorithms That Learn to Control Dynamic Systems Claude Sammut

Experiments on the Costs and Benefits of Windowing in ID3 Jarryl Wirth, Jason Catlett

Extending the Valiant Learning Model Jonathan Amsterdam

Generalizing Number and Learning from Multiple Examples in Explanation Based Learning William W. Cohen

Generalizing the Order of Operators in Macro-Operators Raymond J. Mooney

Hypothesis Filtering: A Practical Approach to Reliable Learning Oren Etzioni

ID5: An Incremental ID3 Paul E. Utgoff

Improved Decision Trees: A Generalized Version of ID3 Jie Cheng, Usama M. Fayyad, Keki B. Irani, Zhaogang Qian

Incremental Multiple Concept Learning Using Experiments Klaus P. Gross

Integrated Learning with Incorrect and Incomplete Theories Michael J. Pazzani

Learning Categorical Decision Criteria in Biomedical Domains Kent A. Spackman

Learning Graph Models of Shape Jakub Segen

Learning Systems of First-Order Rules Nicolas Helft

Learning to Program by Examining and Modifying Cases Robert S. Williams

Machine Invention of First Order Predicates by Inverting Resolution Stephen H. Muggleton, Wray L. Buntine

Midgard: A Genetic Approach to Adaptive Load Balancing for Distributed Systems Adrian V. Sannier Ii, Erik D. Goodman

On Asking the Right Questions Brent J. Krawchuk, Ian H. Witten

On the Tractability of Learning from Incomplete Theories Sridhar Mahadevan, Prasad Tadepalli

Population Size in Classifier Systems George G. Robertson

Reasoning About Operationality for Explanation-Based Learning Haym Hirsh

Reduction: A Practical Mechanism of Searching for Regularity in Data Yi-Hua Wu

Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms Rich Caruana, J. David Schaffer

Some Chunks Are Expensive Milind Tambe, Allen Newell

Some Interesting Properties of a Connectionist Inductive Learning System Edward J. Wisniewski, James A. Anderson

The Interdependencies of Theory Formation, Revision, and Experimentation Brian Falkenhainer, Shankar A. Rajamoney

The Role of Forgetting in Learning Shaul Markovitch, Paul D. Scott

Theory Discovery and the Hypothesis Language Kevin T. Kelly

Trading Off Simplicity and Coverage in Incremental Concept Learning Wayne Iba, James Wogulis, Pat Langley

Tuning Rule-Based Systems to Their Environments Hans Tallis

Two New Frameworks for Learning Balas K. Natarajan, Prasad Tadepalli

Using a Generalization Hierarchy to Learn from Examples Randy Kerber

Using Experience-Based Learning in Game Playing Kenneth A. De Jong, Alan C. Schultz

Using Weighted Networks to Represent Classification Knowledge in Noisy Domains Ming Tan, Larry J. Eshelman

Utilizing Experience for Improving the Tactical Manager Michael D. Erickson, Jan M. Zytkow