Titlebook: Computational Architectures Integrating Neural and Symbolic Processes; A Perspective on the Ron Sun,Lawrence A. Bookman Book 1995 Springer

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Book 1995 research. With the reemergence of neuralnetworks in the 1980s with their emphasis on overcoming some of thelimitations of symbolic AI, there is clearly a need to support someform of high-level symbolic processing in connectionist networks. Asargued by many researchers, on both the symbolic AI and c

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A Two-Level Hybrid Architecture for Structuring Knowledge for Commonsense Reasoningdes in the architecture, inferences are facilitated and knowledge not explicitly encoded in a system can be deduced via a mixture of similarity matching and rule application. The architecture is able to take account of many important desiderata of plausible commonsense reasoning, and produces sensible conclusions.

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A Framework for Integrating Relational and Associational Knowledge for Comprehension deep reading of the text should be able to represent the background details (nonsystematic relationships) associated with the concepts in the text, including the larger frame in which the text concepts are situated.

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Connectionist Natural Language Processing: A Status Reportionist networks are also able to dynamically reinterpret situations as new inputs are received. These features are very useful for natural language processing (NLP) and offer the hope that connectionist approaches to NLP will replace the more traditional, symbolic approaches to NLP.

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