Parallel rewriting in neural networks

Abstract: Rewriting systems are used in various areas of computer science, and especially in lambda-calculus, higher-order 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 first-order 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.