The Integration of Connectionism and First-Order Knowledge Representation and Reasoning as a Challenge for Artificial Intelligence

TitleThe Integration of Connectionism and First-Order Knowledge Representation and Reasoning as a Challenge for Artificial Intelligence
Publication TypeConference Paper
Year of Publication2004
AuthorsSebastian Bader, Steffen Holldobler, Pascal Hitzler
Conference NameThird International Conference on Information
Conference LocationTokyo, Japan
Abstract

Intelligent systems based on first-order logic on the one hand, and on artificial neural networks (also called connectionist systems) on the other, differ substantially. It would be very desirable to combine the robust neural networking machinery with symbolic knowledge representation and reasoning paradigms like logic programming in such a way that the strengths of either paradigm will be retained. Current state-of-the-art research, however, fails by far to achieve this ultimate goal. As one of the main obstacles to be overcome we perceive the question how symbolic knowledge can be encoded by means of connectionist systems: Satisfactory answers to this will naturally lead the way to knowledge extraction algorithms and to integrated neural-symbolic systems.

Full Text

Sebastian Bader, Steffen Holldobler and Pascal Hitzler, 'The Integration of Connectionism and First-Order Knowledge Representation and Reasoning as a Challenge for Artificial Intelligence,' Third International Conference on Information, Tokyo, Japan, November/December 2004, pp. 22-33.
pages: 22-33
year: 2004
venue name: Third International Conference on Information
hasURL: http://knoesis.wright.edu/library/download/0408069v1.pdf

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