Machine learning in video games

<a href="/facts/Artificial_intelligence/lJGauQwX">Artificial intelligence</a> and <a href="/facts/Machine_learning/e0w0XJTu">machine learning</a> techniques are used in <a href="/facts/Video_game/vmTdNASJ">video games</a> for a wide variety of applications such as <a href="/facts/Non-player_character/hg6vxMp5">non-player character</a> (NPC) control, <a href="/facts/Procedural_generation/I94vq0AQ">procedural content generation</a> (PCG) and deep learning-based content generation. <a href="/facts/Machine_learning/e0w0XJTu">Machine learning</a> is a subset of artificial intelligence that uses historical data to build predictive and analytical models. This is in sharp contrast to traditional methods of artificial intelligence such as <a href="/facts/Search_tree/zJIIMEH8">search trees</a> and <a href="/facts/Expert_system/CUCzSEaX">expert systems</a>.
Information on machine learning techniques in the field of games is mostly known to public through <a href="/facts/Research/mo8joeTL">research projects</a> as most gaming companies choose not to publish specific information about their <a href="/facts/Intellectual_property/PqHW9mVP">intellectual property</a>. The most publicly known application of machine learning in games is likely the use of <a href="/facts/Deep_learning/JLuwD3ea">deep learning</a> <a href="/facts/Intelligent_agent/8C2Q93Vw">agents</a> that compete with professional human players in complex <a href="/facts/Strategy_game/96bumhg6">strategy games</a>. There has been a significant application of machine learning on games such as <a href="/facts/Atari/XK95bfqH">Atari</a>/ALE, <a href="/facts/Doom_(1993_video_game)/KA6n0GoY">Doom</a>, <a href="/facts/Minecraft/vwarQdG7">Minecraft</a>, <a href="/facts/StarCraft_(video_game)/FGYVpmR9">StarCraft</a>, and car racing. Other games that did not originally exists as video games, such as chess and Go have also been affected by the machine learning.

Machine learning in video games open-in-new

Machine learning in video games