Game playing has historically provided a measuring stick for artificial intelligence progress due to complex state spaces and rules. Key milestones include TD-Gammon for backgammon using temporal difference reinforcement learning, DeepBlue beating Garry Kasparov in chess using massive parallelism and efficient search, AlphaGo reaching human parity in Go by combining deep learning with Monte Carlo tree sampling, and Libratus exceeding human performance in Poker using structured strategies to handle large, partially observed state spaces.