Model-based methods for board games
Most board games provide a setup that is different from an arcade scenario. The Atari game suite assumes that one player is making decisions in some environment with complex dynamics. By generalizing and learning from the outcome of their actions, the player improves their skills, increasing their final score. In a board game setup, however, the rules of the game are usually quite simple and compact. What makes the game complicated is the number of different positions on the board and the presence of an opponent with an unknown strategy who tries to win the game.
With board games, the ability to observe the game state and the presence of explicit rules opens up the possibility of analyzing the current position, which isn’t the case for Atari. This analysis means taking the current state of the game, evaluating all the possible moves that we can make, and then choosing the best move as our action. To be able to evaluate all the moves...
