Editorial advice to Machine Learning authors
Editorial: Advice to Machine Learning Authors
Learning logical definitions from relations
Learning Logical Definitions from Relations
Empirical Learning as a Function of Concept Character
Empirical learning as a function of concept character
The problem of expensive chunks and its solution by restricting expressiveness
The Problem of Expensive Chunks and its Solution by Restricting Expressiveness
Introduction: Special issue on computational learning theory
Introduction: Special Issue on Computational Learning Theory
Negative Results for Equivalence Queries
Negative results for equivalence queries
Polynomial time learnability of simple deterministic languages
Polynomial Time Learnability of Simple Deterministic Languages
Learning Nested Differences of Intersection-Closed Concept Classes
Learning nested differences of intersection-closed concept classes
The strength of weak learnability
The Strength of Weak Learnability
Errata
Editorial
Editorial Exploratory research in machine learning
Extending domain theories: Two case studies in student modeling
Extending Domain Theories: Two Case Studies in Student Modeling
Acquiring Recursive and Iterative Concepts with Explanation-Based Learning
Acquiring recursive and iterative concepts with explanation-based learning
Boolean Feature Discovery in Empirical Learning
Boolean feature discovery in empirical learning
A necessary condition for learning from positive examples
A Necessary Condition for Learning from Positive Examples
Announcements
Introduction
Introduction
Learning Sequential Decision Rules Using Simulation Models and Competition
Learning sequential decision rules using simulation models and competition
CSM: A Computational Model of Cumulative Learning
CSM: A computational model of cumulative learning
Probability Matching, the Magnitude of Reinforcement, and Classifier System Bidding
Probability matching, the magnitude of reinforcement, and classifier system bidding
Empirical learning using rule threshold optimization for detection of events in synthetic images
Empirical Learning Using Rule Threshold Optimization for Detection of Events in Synthetic Images
Call for papers for ICGA-91
