Connectionist model generation: A first-order approach
نویسندگان
چکیده
منابع مشابه
Connectionist model generation: A first-order approach
Knowledge based artificial neural networks have been applied quite successfully to propositional knowledge representation and reasoning tasks. However, as soon as these tasks are extended to structured objects and structure-sensitive processes as expressed e.g., by means of first-order predicate logic, it is not obvious at all what neural symbolic systems would look like such that they are trul...
متن کاملThe Core Method: Connectionist Model Generation for First-Order Logic Programs
Research into the processing of symbolic knowledge by means of connectionist networks aims at systems which combine the declarative nature of logicbased artificial intelligence with the robustness and trainability of artificial neural networks. This endeavour has been addressed quite successfully in the past for propositional knowledge representation and reasoning tasks. However, as soon as the...
متن کاملIntegrating First-Order Logic Programs and Connectionist Systems — A Constructive Approach
Significant advances have recently been made concerning the integration of symbolic knowledge representation with artificial neural networks (also called connectionist systems). However, while the integration with propositional paradigms has resulted in applicable systems, the case of first-order knowledge representation has so far hardly proceeded beyond theoretical studies which prove the exi...
متن کاملA Fully Connectionist Model Generator for Covered First-Order Logic Programs
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples, we embed the associated semantic operator into a feed-forward network and train the network using the examples. This results in the learning of first-order knowledge while damaged or noisy data is handled gracefully.
متن کاملThe Core Method: Connectionist Model Generation
Knowledge based artificial networks networks have been applied quite successfully to propositional knowledge representation and reasoning tasks. However, as soon as these tasks are extended to structured objects and structure-sensitive processes it is not obvious at all how neural symbolic systems should look like such that they are truly connectionist and allow for a declarative reading at the...
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ژورنال
عنوان ژورنال: Neurocomputing
سال: 2008
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2007.10.028