Reasoning, nonmonotonicity and learning in connectionist networks that capture propositional knowledge

DOI10.1016/0004-3702(94)00032-VzbMath1013.68505MaRDI QIDQ1855237

Gadi Pinkas

Publication date: 4 February 2003

Published in: Artificial Intelligence (Search for Journal in Brave)

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Logic in artificial intelligence (68T27) Logic in computer science (03B70)

Related Items (12)

How to decide what to do? ⋮ Nonmonotonic inferences and neural networks ⋮ Logic tensor networks ⋮ Improved training of physics-informed neural networks for parabolic differential equations with sharply perturbed initial conditions ⋮ Sequential inference with reliable observations: Learning to construct force-dynamic models ⋮ Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations ⋮ Artificial nonmonotonic neural networks ⋮ Weighted defeasible knowledge bases and a multipreference semantics for a deep neural network model ⋮ Recurrent neural networks with backtrack-points and negative reinforcement applied to cost-based abduction ⋮ Logic and Complexity in Cognitive Science ⋮ \(\text{DA}^2\) merging operators ⋮ Compiling propositional weighted bases

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