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DeepGamingAI's video: Deploying Trained RL Agents To Visually Different Games Game Futurology 17

@Deploying Trained RL Agents To Visually Different Games | Game Futurology #17
This is episode of the video series "Game Futurology" covering the paper "Self-Supervised Policy Adaptation during Deployment" by Nicklas Hansen, Yu Sun, Pieter Abbeel, Alexei A. Efros, Lerrel Pinto and Xiaolong Wang. PDF: https://arxiv.org/pdf/2007.04309.pdf Code: https://github.com/nicklashansen/policy-adaptation-during-deployment Authors' Blog Post: https://nicklashansen.github.io/PAD/ Game Futurology: This is a video series consisting of short 2-3 minute overview of research papers in the field of AI and Game Development. This series aims to ponder over what the future games might look like based on the latest academic research going on in the field today. Subscribe for more weekly videos! Abstract: In most real world scenarios, a policy trained by reinforcement learning in one environment needs to be deployed in another, potentially quite different environment. However, generalization across different environments is known to be hard. A natural solution would be to keep training after deployment in the new environment, but this cannot be done if the new environment offers no reward signal. Our work explores the use of self-supervision to allow the policy to continue training after deployment without using any rewards. While previous methods explicitly anticipate changes in the new environment, we assume no prior knowledge of those changes yet still obtain significant improvements. Empirical evaluations are performed on diverse environments from DeepMind Control suite and ViZDoom. Our method improves generalization in 25 out of 30 environments across various tasks, and outperforms domain randomization on a majority of environments. Music Credits: https://www.fesliyanstudios.com/ ---------------------------------------------------------------- • YouTube - https://www.youtube.com/c/DeepGamingA... • Twitter - https://twitter.com/deepgamingai • Medium - https://medium.com/@chintan.t93 • GitHub - https://github.com/ChintanTrivedi --------------------------------------------------------------------

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This video was published on 2020-07-17 19:07:40 GMT by @DeepGamingAI on Youtube. DeepGamingAI has total 5.4K subscribers on Youtube and has a total of 71 video.This video has received 31 Likes which are lower than the average likes that DeepGamingAI gets . @DeepGamingAI receives an average views of 2.1K per video on Youtube.This video has received 7 comments which are lower than the average comments that DeepGamingAI gets . Overall the views for this video was lower than the average for the profile.DeepGamingAI #17 #ArtificialIntelligence #MachineLearning #GameDevelopment #ReinforcementLearning #ComputerVision has been used frequently in this Post.

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