I learned about Adversarial Search. Whereby, it is part of the development of Artificial Intelligence (AI) in playing games. There are two kinds of games, Deterministic and non-deterministic. In deterministic games, the first method is the Minimax Algorithm. Which case it uses a search tree visualization with each concurrent depth being the alternate steps done by players. The algorithm finds the biggest number for the player (meaning most likely step so that the player will win) and the lowest number for opponent. A supposed upgraded version would be Alpha-Beta Pruning whereby it assumes that the opponent is as intelligent and also it cuts unnecessary steps that the player will and supposedly should not take. This limits the vastness of option in the search tree when playing complex game such as chess. In non-deterministic, there is a different type of node for the previous method, which is a chance node as the game itself is non-deterministic.