Neural networks Artificial intelligence

a neural network interconnected group of nodes, akin vast network of neurons in human brain.

neural networks modeled after neurons in human brain, trained algorithm determines output response input signals. study of non-learning artificial neural networks began in decade before field of ai research founded, in work of walter pitts , warren mccullouch. frank rosenblatt invented perceptron, learning network single layer, similar old concept of linear regression. pioneers include alexey grigorevich ivakhnenko, teuvo kohonen, stephen grossberg, kunihiko fukushima, christoph von der malsburg, david willshaw, shun-ichi amari, bernard widrow, john hopfield, eduardo r. caianiello, , others.

the main categories of networks acyclic or feedforward neural networks (where signal passes in 1 direction) , recurrent neural networks (which allow feedback , short-term memories of previous input events). among popular feedforward networks perceptrons, multi-layer perceptrons , radial basis networks. neural networks can applied problem of intelligent control (for robotics) or learning, using such techniques hebbian learning, gmdh or competitive learning.

today, neural networks trained backpropagation algorithm, had been around since 1970 reverse mode of automatic differentiation published seppo linnainmaa, , introduced neural networks paul werbos.

hierarchical temporal memory approach models of structural , algorithmic properties of neocortex.