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Two Minute Papers · 发布于 2016年5月19日
In this piece of work, a combination of deep learning and reinforcement learning is presented which has proven to be useful in solving many extremely difficult tasks. Google DeepMind built a system that can play Atari games at a superhuman level using this technique that is also referred to as Deep Q-Learning. This time, it was used to teach digital creatures to walk and overcome challenging terrain arrangements. __________________________ The paper "Terrain-Adaptive Locomotion Skills Using Deep Reinforcement Learning " is available here: http://www.cs.ubc.ca/~van/papers/2016-TOG-deepRL/index.html The implementation of the paper is also available here: https://github.com/xbpeng/DeepTerrainRL OpenAI's Gym project: https://gym.openai.com/ WE WOULD LIKE TO THANK OUR GENEROUS SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Sunil Kim. https://www.patreon.com/TwoMinutePapers Subscribe if you would like to see more of these! - http://www.youtube.com/subscription_center?add_user=keeroyz The thumbnail background image was created by Fulvio Spada - https://flic.kr/p/o7z8o1 Splash screen/thumbnail design: Felícia Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Facebook → https://www.facebook.com/TwoMinutePapers/ Twitter → https://twitter.com/karoly_zsolnai Web → https://cg.tuwien.ac.at/~zsolnai/
