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  2. Machine learning in video games - Wikipedia

    en.wikipedia.org/.../Machine_learning_in_video_games

    The most publicly known application of machine learning in games is likely the use of deep learning agents that compete with professional human players in complex strategy games. There has been a significant application of machine learning on games such as Atari/ALE, Doom, Minecraft, StarCraft, and car racing. [1]

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  4. Quick, Draw! - Wikipedia

    en.wikipedia.org/wiki/Quick,_Draw!

    Quick, Draw! is an online guessing game developed and published by Google LLC that challenges players to draw a picture of an object or idea and then uses a neural network artificial intelligence to guess what the drawings represent. [2] [3] [4] The AI learns from each drawing, improving its ability to guess correctly in the future. [3]

  5. Iconary - Wikipedia

    en.wikipedia.org/wiki/Iconary

    Iconary is an AI-driven, Pictionary-style online game developed at the Allen Institute for Artificial Intelligence. Publicly released in February 2019, the game is designed to encourage collaborative communication between a human player and the AI player AllenAI. Iconary is the first demonstration of an AI system capable of playing a Pictionary ...

  6. Virtual private network - Wikipedia

    en.wikipedia.org/wiki/Virtual_private_network

    Virtual private network (VPN) is a network architecture for virtually extending a private network (i.e. any computer network which is not the public Internet) across one or multiple other networks which are either untrusted (as they are not controlled by the entity aiming to implement the VPN) or need to be isolated (thus making the lower network invisible or not directly usable).

  7. Arthur Samuel (computer scientist) - Wikipedia

    en.wikipedia.org/wiki/Arthur_Samuel_(computer...

    Arthur Lee Samuel (December 5, 1901 – July 29, 1990) [3] was an American pioneer in the field of computer gaming and artificial intelligence. [2] He popularized the term "machine learning" in 1959. [4]

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  9. Statistical learning theory - Wikipedia

    en.wikipedia.org/wiki/Statistical_learning_theory

    Supervised learning involves learning from a training set of data. Every point in the training is an input–output pair, where the input maps to an output. The learning problem consists of inferring the function that maps between the input and the output, such that the learned function can be used to predict the output from future input.