Deep Reinforcement Learning in Action

A.3. Deep learning

A deep neural network is simply a composition of multiple layers of simpler functions called layers. Each layer function consists of a matrix multiplication followed by a nonlinear activation function. The most common activation function is f(x) = max(0,x), which returns 0 if x is negative or returns x otherwise.

A simple neural network might be

Read this diagram from left to right as if data flows in from the left into the L1 function then the L2 function and becomes the output on the right. The symbols k, m, and n refer to the dimensionality of the vectors. A k-length vector is input to function L1, which produces an m-length ...