Dimensions of Neural-symbolic Integration - A Structured Survey

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dc.creatorBader, Sebastian
dc.creatorHitzler, Pascal
dc.date2005-11-10
dc.date.accessioned2026-07-07T06:49:35Z
dc.date.available2026-07-07T06:49:35Z
dc.descriptionResearch on integrated neural-symbolic systems has made significant progress in the recent past. In particular the understanding of ways to deal with symbolic knowledge within connectionist systems (also called artificial neural networks) has reached a critical mass which enables the community to strive for applicable implementations and use cases. Recent work has covered a great variety of logics used in artificial intelligence and provides a multitude of techniques for dealing with them within the context of artificial neural networks. We present a comprehensive survey of the field of neural-symbolic integration, including a new classification of system according to their architectures and abilities.
dc.description28 pages
dc.identifierhttps://arxiv.org/abs/cs/0511042
dc.identifierhttp://arxiv.org/abs/cs/0511042
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/104400
dc.subjectArtificial Intelligence
dc.subjectLogic in Computer Science
dc.subjectNeural and Evolutionary Computing
dc.titleDimensions of Neural-symbolic Integration - A Structured Survey
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