Neural networks and logical reasoning systems. A translation table
Joao Martins, R. Vilela Mendes
Abstract
A correspondence is established between the elements of logic reasoning systems (knowledge bases, rules, inference and queries) and the hardware and dynamical operations of neural networks. The correspondence is framed as a general translation dictionary which, hopefully, will allow to go back and forth between symbolic and network formulations, a desirable step in learning-oriented systems and multicomputer networks. In the framework of Horn clause logics it is found that atomic propositions with n arguments correspond to nodes with n-th order synapses, rules to synaptic intensity constraints, forward chaining to synaptic dynamics and queries either to simple node activation or to a query tensor dynamics.
Create a lesson
Related papers
Testing Replica Symmetry Breaking in the three-dimensional Edwards-Anderson model by using vanishing fields
Miguel Aguilar-Janita, Silvio Franz, Victor Martin-Mayor et al.
Deep Learning of Phase Transitions for Bilinear-Biquadratic Spin-1 Chains from Correlation Aspects
Ming-Chiang Chung, Yu-Ting Kuo, Ian McCulloch et al.
Resolving Structural Uncertainty in Stochastic Dynamical Systems via Ensemble-Based Bayesian Inference
Francesco Zambelli, Valeria D'Andrea, Manlio De Domenico
Seismology of Glasses
Zhiyu Cao, Peter G. Wolynes
Orbital cancellation and reentrant localization in a quasiperiodic trimer ladder
Xin Wang, Pei-Jie Chang, Quanfeng Lu et al.
Quantum Localization in Geometric Complex Networks
Jan Lewenstein-Sanpera, Tobias Grass, M. Àngeles Serrano et al.