Boltzmann Machine and Hyperbolic activation function in Higher Order Neuro Symbolic Integration

Muraly Velavan, Zainor Ridzuan bin Yahya, Mohamad Nazri bin Abdul Halif, Saratha Sathasivam
2015 International journal of computational and electronics aspects in engineering  
Higher-order network structure isimportant in doing higher order programming because high-order neural networks have converge faster and have a higher memory and story capacity. Furthermore higher order networks also have higher approximation ability and robust if compare lower-order neural networks. Thus, the higher-order clauses for logic programming in Hopfield Networks are been focused in this paper. We will limit till fifth order network due to complexity issue. Hereby we employed
more » ... Machines and hyperbolic tangent activation function to increased the performance of neuro symbolic integration. We used agent based modelling to model this problem. Index terms -Boltzmann machine, agent based modelling and hyperbolic tangent activation function I.
doi:10.26706/ijceae.1.1.20150103 fatcat:6piw6wvbjbapjji2g7rpu4yc7a