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Unification Neural Networks: Unification by ErrorCorrection Learning
"... We show that the conventional firstorder algorithm of unification can be simulated by finite artificial neural networks with one layer of neurons. In these unification neural networks, the unification algorithm is performed by errorcorrection learning. Each timestep of adaptation of the network c ..."
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We show that the conventional firstorder algorithm of unification can be simulated by finite artificial neural networks with one layer of neurons. In these unification neural networks, the unification algorithm is performed by errorcorrection learning. Each timestep of adaptation of the network corresponds to a single iteration of the unification algorithm. We present this result together with the library of learning functions and examples fully formalised in MATLAB Neural Network Toolbox.
Parallel rewriting in neural networks
 In Proceedings of ICNC’09
, 2009
"... Abstract: Rewriting systems are used in various areas of computer science, and especially in lambdacalculus, higherorder logics and functional programming. We show that the unsupervised learning networks can implement parallel rewriting. We show how this general correspondence can be refined in or ..."
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Abstract: Rewriting systems are used in various areas of computer science, and especially in lambdacalculus, higherorder logics and functional programming. We show that the unsupervised learning networks can implement parallel rewriting. We show how this general correspondence can be refined in order to perform parallel term rewriting in neural networks, for any given firstorder term. We simulate these neural networks in the MATLAB Neural Network Toolbox and present the complete library of functions written in the MATLAB Neural Network Toolbox. 1
Automated Proof Pattern Recognition: the Manual
"... This Documents is a Manual supporting the project Machinelearning coalgebraic automated proofs. Several experiments on patternrecognition of proofpatterns are given here. We provide a method to convert automatically produced prooftrees into ..."
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This Documents is a Manual supporting the project Machinelearning coalgebraic automated proofs. Several experiments on patternrecognition of proofpatterns are given here. We provide a method to convert automatically produced prooftrees into