Basic Mathematics behind Deep Reinforcement Learning
Vinod K. Mishra · 2025
In this chapter, a self-contained exposition of the mathematical basis of deep reinforcement learning is presented. Concepts like reward functions, discount factors, value and policy functions, loss functions, activation functions, etc., are explained and their significance is emphasized. Some analytically solvable models are also given.