In this thesis, we discuss different techniques to bridge the gap between two different approaches to artificial intelligence: the symbolic and the connectionist paradigm. Both approaches have quite contrasting advantages and disadvantages. Research in the area of neural-symbolic integration aims at bridging the gap between them.
Starting from a human readable logic program, we construct connectionist systems, which behave equivalently. Afterwards, those systems can be trained, and later the refined knowledge be extracted.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa.de:bsz:14-qucosa-25468 |
| Date | 15 December 2009 |
| Creators | Bader, Sebastian |
| Contributors | Technische Universität Dresden, Fakultät Informatik, Prof. Dr. rer. nat. habil Steffen Hölldobler, Prof. Dr. rer. nat. habil Barbara Hammer, Prof. Dr. rer. nat. habil Steffen Hölldobler |
| Publisher | Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:doctoralThesis |
| Format | application/pdf, application/pdf, application/zip |
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