Machine Learning（ML ）的JANUARY 1992, ISSUE 1论文列表

卷期号： January 1992, issue 1

发布时间：

卷期年份： 1992

卷期官网： https://link.springer.com/journal/10994/volumes-and-issues/8-1

Learning two-tiered descriptions of flexible concepts: The POSEIDON system

Learning Two-Tiered Descriptions of Flexible Concepts: The POSEIDON System

Implementing Valiant's Learnability Theory Using Random Sets

Implementing Valiant's learnability theory using random sets

A further comparison of splitting rules for decision-tree induction

A Further Comparison of Splitting Rules for Decision-Tree Induction

On the Handling of Continuous-Valued Attributes in Decision Tree Generation

On the handling of continuous-valued attributes in decision tree generation

Call for papers

Editorial

Interactive concept-learning and constructive induction by analogy

Interactive Concept-Learning and Constructive Induction by Analogy

Learning probabilistic automata and Markov chains via queries

Learning Probabilistic Automata and Markov Chains via Queries

Abductive explanation-based learning: A solution to the multiple inconsistent explanation problem

Abductive Explanation-Based Learning: A Solution to the Multiple Inconsistent Explanation Problem

Announcement

Introduction: The challenge of reinforcement learning

Introduction: The Challenge of Reinforcement Learning

Simple statistical gradient-following algorithms for connectionist reinforcement learning

Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning

Practical Issues in Temporal Difference Learning

Practical issues in temporal difference learning

Technical Note: Q-Learning

Q-learning

Self-improving reactive agents based on reinforcement learning, planning and teaching

Self-Improving Reactive Agents Based on Reinforcement Learning, Planning and Teaching

Transfer of Learning by Composing Solutions of Elemental Sequential Tasks

Transfer of learning by composing solutions of elemental sequential tasks

The Convergence of TD(λ) for General λ

The convergence of TD(λ) for general λ

A reinforcement connectionist approach to robot path finding in non-maze-like environments

A Reinforcement Connectionist Approach to Robot Path Finding in Non-Maze-Like Environments