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Lex Fridman · 2018-01-25

MIT 6.S094: Deep Reinforcement Learning

MIT 6.S094: Deep Reinforcement Learning

Also referenced (named, not recommended)

MediaReferenced

Atari Breakout

Atari (inferred)

“some examples we can think of any of the video games some of which we'll talk about today like Atari breakout as the environment the agent is the paddle”— Lex Fridman
MediaReferenced

Doom

id Software (inferred)

“all the first-person shooters the video games is now Starcraft the strategy games in case of first-person shooter and doom what is the goal the environment is the game”— Lex Fridman
MediaReferenced

StarCraft

Blizzard Entertainment (inferred)

“all the first-person shooters the video games is now Starcraft the strategy games in case of first-person shooter and doom what is the goal”— Lex Fridman
MediaReferenced

River Raid

Activision (inferred)

“experience replay when both are used for the game of breakout River raid sea quests and Space Invaders the higher the number the better it is”— Lex Fridman
MediaReferenced

Seaquest

Activision (inferred)

“when both are used for the game of breakout River raid sea quests and Space Invaders the higher the number the better it is the more points achieved”— Lex Fridman
MediaReferenced

Space Invaders

Taito (inferred)

“when both are used for the game of breakout River raid sea quests and Space Invaders the higher the number the better it is the more points achieved”— Lex Fridman