Logic Gates using Neural Networks
Two parts, g and f.
If 'x' values represent all the inputs.
g takes the inputs performs an aggregation function (x1+x2+x3...) on all the inputs.
f makes a decision based on output of g.
An AND function neuron fires only if ALL inputs are 1.
Neuron fires if ANY of the inputs are 1.
Take input as inhibitory function and our threshold is zero.
https://medium.com/autonomous-agents/how-to-teach-logic-to-your-neuralnetworks-116215c71a49 https://towardsdatascience.com/emulating-logical-gates-with-a-neural-network-75c229ec4cc9 https://towardsdatascience.com/neural-representation-of-logic-gates-df044ec922bc