Logic Programming In Neural Networks

Authors

  • Wan Ahmad Tajuddin bin Wan Abdullah University of Malaya

Keywords:

Hopfield neural network, Higher-order connections, Logic program-ming, Combinatorial optimisation, Hebbian learning

Abstract

Logic programming is carried out on a neural network. A higher-order Hopfield neural network is used to minimise logical inconsistency in interpretations of logic clauses or programs. The connection strengths are defined from the logic program; the network relaxes to neural states corresponding to a valid (or near-valid) interpretation. ?Creativity? can be thought of as the crossing of configurational energy barriers to arrive at alternative interpretations. The formalism allows the incorporation of non-monotonicity; non-integral degrees of truth in rules; and non-Horn clauses. Hebbian learning in an environment with some underlying logical rules governing events is equivalent to hardwiring the network with these rules

 

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Published

1996-06-01

How to Cite

bin Wan Abdullah, W. A. T. (1996). Logic Programming In Neural Networks. Malaysian Journal of Computer Science, 9(1), 1–5. Retrieved from https://jrmg.um.edu.my/index.php/MJCS/article/view/2888