Monte Carlo tree search
A search algorithm that uses random simulations to estimate the value of moves. Enabled AlphaGo to evaluate board positions in Go without exhaustive search.
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DeepMind Publishes AlphaGo, a Deep Reinforcement Learning System That Defeated Professional Go Players
In January 2016, researchers at Google DeepMind published a paper in Nature describing AlphaGo, a system combining deep convolutional neural networks with Monte Carlo tree search and reinforcement learning that defeated the European Go champion Fan Hui 5–0, marking the first time a computer program had beaten a professional Go player at full-board Go.