Importance of Self-play and Neural Networks in Game Strategy

The significance of self-play over memorization is underscored by the approach used by AlphaGo. Unlike traditional chess engines, AlphaGo conducts fewer but more intensive evaluations, using a neural network to determine the quality of a position. This method involves passing the board state through a trained neural network to assess if it is a winning or losing state, which consumes more energy but leads to more strategic evaluations.