Recently, model-based reinforcement learning has been considered a crucial approach to applying reinforcement learning in the physical world, primarily due to its efficient utilization of samples.

The most widely used technique for finding the largest or smallest values of a math function turns out to be a fundamentally difficult computational problem. Many aspects of modern applied research ...