enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  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]

  3. Category:Machine learning algorithms - Wikipedia

    en.wikipedia.org/wiki/Category:Machine_learning...

    Download as PDF; Printable version; ... Self-play; Skill chaining; ... Weighted majority algorithm (machine learning) Z. Zero-shot learning

  4. Artificial intelligence in video games - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence_in...

    The term game AI is used to refer to a broad set of algorithms that also include techniques from control theory, robotics, computer graphics and computer science in general, and so video game AI may often not constitute "true AI" in that such techniques do not necessarily facilitate computer learning or other standard criteria, only constituting "automated computation" or a predetermined and ...

  5. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

  6. Proximal policy optimization - Wikipedia

    en.wikipedia.org/wiki/Proximal_Policy_Optimization

    Proximal policy optimization (PPO) is a reinforcement learning (RL) algorithm for training an intelligent agent's decision function to accomplish difficult tasks. PPO was developed by John Schulman in 2017, [1] and had become the default RL algorithm at the US artificial intelligence company OpenAI. [2]

  7. Model-free (reinforcement learning) - Wikipedia

    en.wikipedia.org/wiki/Model-free_(reinforcement...

    Model-free RL algorithms can start from a blank policy candidate and achieve superhuman performance in many complex tasks, including Atari games, StarCraft and Go.Deep neural networks are responsible for recent artificial intelligence breakthroughs, and they can be combined with RL to create superhuman agents such as Google DeepMind's AlphaGo.

  8. General game playing - Wikipedia

    en.wikipedia.org/wiki/General_game_playing

    General game playing (GGP) is the design of artificial intelligence programs to be able to play more than one game successfully. [ 1 ] [ 2 ] [ 3 ] For many games like chess, computers are programmed to play these games using a specially designed algorithm, which cannot be transferred to another context.

  9. Learning classifier system - Wikipedia

    en.wikipedia.org/wiki/Learning_classifier_system

    A step-wise schematic illustrating a generic Michigan-style learning classifier system learning cycle performing supervised learning. Keeping in mind that LCS is a paradigm for genetic-based machine learning rather than a specific method, the following outlines key elements of a generic, modern (i.e. post-XCS) LCS algorithm.