While Google's Deepmind is trying to find out if AI can navigate the complex RTS Starcraft 2, machine learning continues to leap over milestones for traditional strategy board games. AlphaGO is an AI that previously defeated masters of the Chinese game, but that version was given a silver platter of professional and amateur games to study. AlphaGO Zero has
This new version of AlphaGo learned the game via "reinforcement learning" or by playing games against itself. By combining the neural network with a powerful search algorithm, it tunes itself to predict moves and calculate who'll eventually win the match. The updated network is rematched with the algorithm and this rinse/repeat method results in steady improvements. With this process, AlphaGo Zero has defeated the world-champion AlphaGo 100 games to zero. The Deepmind blog listed a few specific ways Zero differs from its older brother:
- AlphaGo Zero only uses the black and white stones from the Go board as its input, whereas previous versions of AlphaGo included a small number of hand-engineered features.
- It uses one neural network rather than two. Earlier versions of AlphaGo used a “policy network” to select the next move to play and a ”value network” to predict the winner of the game from each position. These are combined in AlphaGo Zero, allowing it to be trained and evaluated more efficiently.
- AlphaGo Zero does not use “rollouts” - fast, random games used by other Go programs to predict which player will win from the current board position. Instead, it relies on its high-quality neural networks to evaluate positions.
Google's Deepmind is a leader in AI research, regularly reaching milestones in the field they believe will be one of the most crucial in scientific advances. "AlphaGo Zero also discovered new knowledge, developing unconventional strategies and creative new moves that echoed and surpassed the novel techniques it played in the games against Lee Sedol and Ke Jie," the report reads. "These moments of creativity give us confidence that AI will be a multiplier for human ingenuity, helping us with our mission to solve some of the most important challenges humanity is facing."