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Can we train an AI to complete it's objective in a video game world without needing to build a model of the world before hand? The answer is yes using Q learning! I'll go through several use cases and show some python code of how Q learning works. Code for this video: https://github.com/llSourcell/Q_Learn... Adnan's Winning code: https://github.com/AdnanZahid/Reinfor... Alberto's runner up code: https://github.com/alberduris Please Subscribe! And like. And comment. That's what keeps me going. Want more inspiration & education? Connect with me: Twitter: / sirajraval Facebook: / sirajology More learning resources: http://mnemstudio.org/path-finding-q-... https://ocw.mit.edu/courses/aeronauti... http://uhaweb.hartford.edu/compsci/cc... / deep-reinforcement-learning-demysitifed-ep... https://www.cs.cmu.edu/afs/cs/project... http://cs.stanford.edu/people/karpath... https://www.quora.com/How-is-policy-i... http://www0.cs.ucl.ac.uk/staff/d.silv... Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Instagram: / sirajraval Instagram: / sirajraval Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content! Join my AI community: http://chatgptschool.io/ Sign up for my AI Sports betting Bot, WagerGPT! (500 spots available): https://www.wagergpt.co