CMU Artificial Intelligence Repository
MOBAL: Knowledge Acquisition and Machine Learning System
areas/learning/systems/mobal/
MOBAL is a system for developing operational models of application
domains in a first order logic representation. It integrates a manual
knowledge acquisition and inspection environment, an inference engine,
machine learning methods for automated knowledge acquisition, and a
knowledge revision tool. By using MOBAL's knowledge acquisition
environment, you can incrementally develop a model of your domain in
terms of logical facts and rules. You can inspect the knowledge you
have entered in text or graphics windows, augment the knowledge, or
change it at any time. The built-in inference engine can immediately
execute the rules you have entered to show you the consequences of
your inputs, or answer queries about the current knowledge. MOBAL also
builds a dynamic sort taxonomy from your inputs. If you wish, you can
use several machine learning methods to automatically discover
additional rules based on the facts that you have entered, or to form
new concepts. If there are contradictions in the knowledge base due to
incorrect rules or facts, there is a knowledge revision tool to help
you locate the problem and fix it.
MOBAL includes a graphical interface implemented using Tcl/TK.
Since the very first releases, MOBAL has been a kind of toolbox
offering different tools (including the Rule Discovery Tool RDT) to
support the modeling of domains. Now we have coupled MOBAL with some
other well known ILP systems. The new release contains interfaces to
and the code of following learning systems:
- FOIL 5 (J. Ross Quinlan),
- GOLEM (S. Muggleton and C. Feng),
- mFOIL (S. Dzeroski and I. Bratko),
- CILGG (J.-U. Kietz), and
- INCY (E. Sommer).
Origin:
ftp.gmd.de:/gmd/mlt/Mobal/
Version: 3.0b
Ports: Sun Sparc (SunOS 4.1)
Copying: Copyright (c) 1989-94 by GMD
Use, copy, and distribution permitted for academic,
education, and non-commercial uses.
Please send a message to mobal@gmd.de if you are using
MOBAL.
CD-ROM: Prime Time Freeware for AI, Issue 1-1
Bug Reports: mobal@gmd.de
Contact: Project MLT
GMD (German National Research Center for Computer Science)
AI Research Division (I3.KI)
Schloss Birlinghoven
D 53757 St. Augustin
Germany
Fax: +49/2241/14-2889
Keywords:
GMD, Inference Engines, Knowledge Acquisition, MOBAL,
Machine Learning!Inductive Learning
References: ?
Last Web update on Mon Feb 13 10:24:32 1995
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