Learning light transport the reinforced way

We introduce a rendering algorithm that is as simple as a path tracer but dramatically improves light transport simulation and even outperforms the Metropolis light transport algorithm. The underlying method of importance sampling learns where radiance is coming from and in fact coincides with reinforcement learning. The cost for the improvement is a data structure similar to irradiance volumes as used in realtime games.