Gradient based optimizers are algorithms that use the gradient of a funciton to iteratively find locally extreme points of functions over a set of parameters. This sections provides a description of a set of gradient optimizers. The optimizers are written with boost::math::differentiation::reverse_mode::rvar in mind, however if a way to evaluate the funciton and its gradient is provided, the optimizers should work in exactly the same way.