Function Approximation using Tile Coding

The "learning" (i.e. iterative updating of the weights corresponding to the binary tile features) proceeds by - in each iteration - selecting an (x, y) point at random and using the true Rosenbrock function as update target. The stepsize parameter alpha was set to 0.1.
The animation was made in Python using matplotlib's plot_surface function.