Extracting Propositional Logic Programs From Neural Networks: A Decompositional Approach.
From International Center for Computational Logic
Extracting Propositional Logic Programs From Neural Networks: A Decompositional Approach.
Bachelor's thesis, project thesis by Valentin Mayer-Eichberger
- Supervisor Steffen Hölldobler, Sebastian Bader
- Wissensverarbeitung
- 24 Januar 2006 – 24 Januar 2006
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Combining artificial neural networks and logic programming for machine
learning tasks is the main objective of neural symbolic integration. One
important step towards practical applications in this field is the development
of techniques for extracting symbolic knowledge from neural networks.
In this thesis a new extraction method is proposed and thoroughly investigated.
It translates the class of feedforward networks with binary threshold
functions into propositional logic programs by means of a decompositional
approach.
