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  2. Deep reinforcement learning - Wikipedia

    en.wikipedia.org/wiki/Deep_reinforcement_learning

    All 49 games were learned using the same network architecture and with minimal prior knowledge, outperforming competing methods on almost all the games and performing at a level comparable or superior to a professional human game tester. [15] Deep reinforcement learning reached another milestone in 2015 when AlphaGo, [16] a computer program ...

  3. AlphaGo - Wikipedia

    en.wikipedia.org/wiki/AlphaGo

    AlphaGo is a computer program that plays the board game Go. [1] It was developed by the London-based DeepMind Technologies, [2] an acquired subsidiary of Google.Subsequent versions of AlphaGo became increasingly powerful, including a version that competed under the name Master. [3]

  4. Self-play - Wikipedia

    en.wikipedia.org/wiki/Self-play

    In multi-agent reinforcement learning experiments, researchers try to optimize the performance of a learning agent on a given task, in cooperation or competition with one or more agents. These agents learn by trial-and-error, and researchers may choose to have the learning algorithm play the role of two or more of the different agents.

  5. AlphaDev - Wikipedia

    en.wikipedia.org/wiki/AlphaDev

    AlphaDev is an artificial intelligence system developed by Google DeepMind to discover enhanced computer science algorithms using reinforcement learning.AlphaDev is based on AlphaZero, a system that mastered the games of chess, shogi and go by self-play.

  6. MuZero - Wikipedia

    en.wikipedia.org/wiki/MuZero

    MuZero (MZ) is a combination of the high-performance planning of the AlphaZero (AZ) algorithm with approaches to model-free reinforcement learning. The combination allows for more efficient training in classical planning regimes, such as Go, while also handling domains with much more complex inputs at each stage, such as visual video games.

  7. AlphaZero - Wikipedia

    en.wikipedia.org/wiki/AlphaZero

    AlphaZero is a generic reinforcement learning algorithm – originally devised for the game of go – that achieved superior results within a few hours, searching a thousand times fewer positions, given no domain knowledge except the rules."

  8. Reinforcement learning - Wikipedia

    en.wikipedia.org/wiki/Reinforcement_learning

    Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal. Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised ...

  9. Monte Carlo tree search - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_tree_search

    The rating of best Go-playing programs on the KGS server since 2007. Since 2006, all the best programs use Monte Carlo tree search. [14]In 2006, inspired by its predecessors, [15] Rémi Coulom described the application of the Monte Carlo method to game-tree search and coined the name Monte Carlo tree search, [16] L. Kocsis and Cs.