Note on MiniMax (Updating) Motivation This is a very traditional way of solving turn based game like chess or tic-tac-toc. It’s climax is Deep Blue AI in playing chess. Note, some people think about GAN training procedure as a min-max game between G and D, which is also interesting.
May 18, 2020
Reinforcement Learning deals with environment and rewards. Agents have a set of actions to interact with environment (state $s_i$), and the environment will be changed by these actions $a_j$, from time to time, there will be reward coming from environment!
Mar 20, 2020