John E. Laird
Proceedings of the Fifth International Workshop on Machine Learning
ML, 1988.

@proceedings{ML-1988,
	address       = "Ann Arbor, Michigan, USA",
	editor        = "John E. Laird",
	isbn          = "0-934613-64-8",
	publisher     = "{Morgan Kaufmann}",
	title         = "{Proceedings of the Fifth International Workshop on Machine Learning}",
	year          = 1988,
}

Contents (49 items)

20 ×#learning
6 ×#approach
5 ×#classification
5 ×#concept
5 ×#named
5 ×#using
3 ×#incremental
3 ×#multi
3 ×#search-based
2 ×#algorithm

ML-1988-Kerber #using

Using a Generalization Hierarchy to Learn from Examples (RK), pp. 1–7.

ML-1988-Tallis #rule-based

Tuning Rule-Based Systems to Their Environments (HT), pp. 8–14.

ML-1988-KrawchukW #on the

On Asking the Right Questions (BJK, IHW), pp. 15–21.

ML-1988-FisherS #concept #predict

Concept Simplification and Prediction Accuracy (DHF, JCS), pp. 22–28.

ML-1988-Segen #graph #learning #modelling

Learning Graph Models of Shape (JS), pp. 29–35.

ML-1988-Spackman #category theory #learning

Learning Categorical Decision Criteria in Biomedical Domains (KAS), pp. 36–46.

ML-1988-Segen88a #concept

Conceptual Clumping of Binary Vectors with Occam’s Razor (JS), pp. 47–53.

ML-1988-CheesemanKSSTF #classification #named

AutoClass: A Bayesian Classification System (PC, JK, MS, JS, WT, DF), pp. 54–64.

ML-1988-Gross #concept #incremental #learning #multi #using

Incremental Multiple Concept Learning Using Experiments (KPG), pp. 65–72.

ML-1988-IbaWL #concept #incremental #learning

Trading Off Simplicity and Coverage in Incremental concept Learning (WI, JW, PL), pp. 73–79.

ML-1988-Lebowitz

Deferred Commitment in UNIMEM: Waiting to Learn (ML), pp. 80–86.

ML-1988-WirthC #cost analysis

Experiments on the Costs and Benefits of Windowing in ID3 (JW, JC), pp. 87–99.

ML-1988-ChengFIQ

Improved Decision Trees: A Generalized Version of ID3 (JC, UMF, KBI, ZQ), pp. 100–106.

ML-1988-Utgoff #incremental #named

ID5: An Incremental ID3 (PEU), pp. 107–120.

ML-1988-TanE #classification #network #using

Using Weighted Networks to Represent Classification Knowledge in Noisy Domains (MT, LJE), pp. 121–134.

ML-1988-Quinlan #classification #comparison #empirical #search-based

An Empirical Comparison of Genetic and Decision-Tree Classifiers (JRQ), pp. 135–141.

ML-1988-Robertson #classification

Population Size in classifier Systems (GGR), pp. 142–152.

ML-1988-CaruanaS #algorithm #bias #representation #search-based

Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms (RC, JDS), pp. 153–161.

ML-1988-DavisY #classification

Classifier Systems with Hamming Weights (LD, DKY), pp. 162–173.

ML-1988-SannierG #adaptation #approach #distributed #named #search-based

Midgard: A Genetic Approach to Adaptive Load Balancing for Distributed Systems (AVSI, EDG), pp. 174–180.

ML-1988-WisniewskiA #induction #learning

Some Interesting Properties of a Connectionist Inductive Learning System (EJW, JAA), pp. 181–187.

ML-1988-Lynne #learning

Competitive Reinforcement Learning (KJL), pp. 188–199.

ML-1988-Tesauro #learning

Connectionist Learning of Expert Backgammon Evaluations (GT), pp. 200–206.

ML-1988-Mel #modelling #using

Building and Using Mental Models in a Sensory-Motor Domain (BWM), pp. 207–213.

ML-1988-Hirsh #learning #reasoning

Reasoning about Operationality for Explanation-Based Learning (HH), pp. 214–220.

ML-1988-BravermanR #bound

Boundaries of Operationality (MSB, SJR), pp. 221–234.

ML-1988-MahadevanT #learning #on the

On the Tractability of Learning from Incomplete Theories (SM, PT), pp. 235–241.

ML-1988-RajamoneyD #approach #multi #problem #reduction

Active Explanation Reduction: An Approach to the Multiple Explanations Problem (SAR, GD), pp. 242–255.

ML-1988-Cohen #learning #multi

Generalizing Number and Learning from Multiple Examples in Explanation Based Learning (WWC), pp. 256–269.

ML-1988-Mooney #order

Generalizing the Order of Operators in Macro-Operators (RJM), pp. 270–283.

ML-1988-JongS #game studies #learning #using

Using Experience-Based Learning in Game Playing (KADJ, ACS), pp. 284–290.

ML-1988-Pazzani #learning

Integrated Learning with Incorrect and Incomplete Theories (MJP), pp. 291–297.

ML-1988-Carpineto #approach #generative #learning

An Approach Based on Integrated Learning to Generating Stories (CC), pp. 298–304.

ML-1988-BergadanoG #approach #concept #induction

A Knowledge Intensive Approach to Concept Induction (FB, AG), pp. 305–317.

ML-1988-Williams #learning

Learning to Program by Examining and Modifying Cases (RSW), pp. 318–324.

ML-1988-Kelly

Theory Discovery and the Hypothesis Language (KTK), pp. 325–338.

ML-1988-MuggletonB #first-order

Machine Invention of First Order Predicates by Inverting Resolution (SM, WLB), pp. 339–352.

ML-1988-FalkenhainerR

The Interdependencies of Theory Formation, Revision, and Experimentation (BF, SAR), pp. 353–366.

ML-1988-RoseL #approach

A Hill-Climbing Approach to Machine Discovery (DR, PL), pp. 367–373.

ML-1988-Wu #named #reduction

Reduction: A Practical Mechanism of Searching for Regularity in Data (YHW), pp. 374–380.

ML-1988-Amsterdam #learning

Extending the Valiant Learning Model (JA), pp. 381–394.

ML-1988-Helft #first-order #learning

Learning Systems of First-Order Rules (NH), pp. 395–401.

ML-1988-NatarajanT #framework #learning

Two New Frameworks for Learning (BKN, PT), pp. 402–415.

ML-1988-Etzioni #approach #learning #reliability

Hypothesis Filtering: A Practical Approach to Reliable Learning (OE), pp. 416–429.

ML-1988-Kadie #learning #named

Diffy-S: Learning Robot Operator Schemata from Examples (CMK), pp. 430–436.

ML-1988-Sammut #algorithm #evaluation

Experimental Results from an Evaluation of Algorithms that Learn to Control Dynamic Systems (CS), pp. 437–443.

ML-1988-EricksonZ #experience

Utilizing Experience for Improving the Tactical Manager (MDE, JMZ), pp. 444–450.

ML-1988-TambeN

Some Chunks Are Expensive (MT, AN), pp. 451–458.

ML-1988-MarkovitchS #learning

The Role of Forgetting in Learning (SM, PDS), pp. 459–465.