CMU Artificial Intelligence Repository
Machine Learning Algorithms Implemented in Prolog
areas/learning/systems/learn_pl/
aq1/ AQ-Prolog: Reimplementation of Michalski's AQ for
attribute vectors
arch1/ ARCH1: Winston's incremental learning procedure.
arch2/ ARCH2: Winston's incremental learning procedure.
attdsc/ ATTDSC: Bratko's simple algorithm for
attributional descriptions.
cobweb/ COBWEB: Gennari, Langley, and Fisher's
incremental concept formation algorithm.
discr/ DISCR: Generation of discriminants from
derivation trees.
ebg/ EBG: Explanation Based Generalization
idt/ IDT: Torgos ID3-like system based on the
gain-ratio measure
invers/ INVERS: Two versions of the two main operators
for inverse resolution.
logic/ Logic procedures that are useful for learning
multagnt/ MULTAGNT: Brazdil's Simulation of a tutoring
setting between two agents
vs/ Version Spaces
Origin:
ftp.gmd.de:/gmd/mlt/ML-Program-Library/ [129.26.8.84]
In 1988 the Special Interest Group on Machine Learning of the German
Society for Computer Science (GI e.V.) decided to establish a library
of PROLOG implementations of Machine Learning algorithms. The library
includes - amongst others - PROLOG implementations of Winston's arch,
Becker's AQ-PROLOG, Fisher's COBWEB, Brazdil's generation of
discriminations from derivation trees, Quinlan's ID3, FOIL, IDT,
substitution matching, explanation based generalization, inverse
resolution, and Mitchell's version spaces algorithm. Most of the
algorithms are copyleft under the GNU General Public License.
They are also available by surface mail from Thomas Hoppe (see address
below). Files will be distributed via MS-DOS formated 3.5 inch floppy
(double, high and extra-high density), which should be included with
your request. You can also get them by sending an email message to
Thomas Hoppe.
Send additional PROLOG implementations of Machine Learning
Algorithms, complaints about them and detected bugs or problems
to Thomas Hoppe. Send suggestions and complaints about the ftp
library to Werner Emde.
The directory ftp.gmd.de:/MachineLearning/ contains additional
machine learning publications, data, and software, primarily related
to the European ESPRIT projects Machine Learning Toolbox (MLT) and
Inductive Logic Programming (ILP), the European Network of Excellence
in Machine Learning (MLnet) and the Inductive Logic Programming
Pan-European Scientific Network (ILPnet). It includes the source code
of Stephen Muggleton's and Cao Feng's GOLEM learning system (in
/MachineLearning/ILP/public/software/golem) and a BibTeX file with
around 325 entries of articles related to ILP (in
/MachineLearning/ILP/public/bib). For more information, send mail to
Marcus Luebbe .
Version: 9-FEB-94
Requires: Prolog
Ports: All of the algorithms are written in Edinburgh Prolog syntax.
Copying: GNU GPL
CD-ROM: Prime Time Freeware for AI, Issue 1-1
Contact: Thomas Hoppe (Machine Learning Library)
Projektgruppe KIT
Technische Universitaet Berlin
Franklinstr. 28/29,
10629 Berlin, Germany.
Werner Emde (ftp library)
Gesellschaft fuer Mathematik und Datenverarbeitung, Bonn
Keywords:
AQ-Prolog, COBWEB, Derivation Trees, Discriminants, EBG,
FOIL, GNU GPL, ID3, IDT, Inverse Resolution,
Machine Learning, Mitchell, Prolog!Code,
Substitution Matching, Version Spaces, Winston's Arch
Last Web update on Mon Feb 13 10:24:30 1995
AI.Repository@cs.cmu.edu