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MOBAL: Knowledge Acquisition and Machine Learning System

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).

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 if you are using MOBAL. CD-ROM: Prime Time Freeware for AI, Issue 1-1 Bug Reports: 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: ?
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