reinfocement learning
TRANSCRIPT
© 2016. SNU CSE Biointelligence Lab., http://bi.snu.ac.kr1
Introduction of Reinforcement Learn-ing
곽동현
서울대학교 바이오지능 연구실
© 2016. SNU CSE Biointelligence Lab., http://bi.snu.ac.kr2
Background• 기존의 강화학습 (Reinforcement Learning) 에서 Q func-
tion 을 DNN 혹은 CNN 으로 근사하여 문제를 해결하는 시도가 최근 Google DeepMind 를 필두로 활발히 연구가 되고 있다 .
• 최근 연구에서는 Atari 2600, 바둑을 인간보다 더 잘 플레이하는 수준의 경이적인 성과를 보이고 있으며 , 나아가 3D 게임이나 로봇 컨트롤 문제에도 적용되고 있다 .
© 2016. SNU CSE Biointelligence Lab., http://bi.snu.ac.kr3
What is AI? ML?
https://www.linkedin.com/pulse/deep-dive-venture-landscape-ai-ajit-nazre-rahul-garg-nazre
© 2016. SNU CSE Biointelligence Lab., http://bi.snu.ac.kr4
Various Field with ML
https://www.linkedin.com/pulse/how-exceed-your-goals-2016-dr-travis-bradberry-1
© 2016. SNU CSE Biointelligence Lab., http://bi.snu.ac.kr6
Function Approximation
http://arxiv.org/pdf/1411.4555.pdf https://people.mpi-inf.mpg.de/~kkim/supres/supres.htm
© 2016. SNU CSE Biointelligence Lab., http://bi.snu.ac.kr8
Machine Learning• Supervised Learning :
y = f(x)
• Unsupervised Learning : x ~ p(x) , x = f(x)
• Reinforcement Learning : ??
© 2016. SNU CSE Biointelligence Lab., http://bi.snu.ac.kr9
Agent-Environment Interaction
• Objective : Maximize the expected sum of future rewards
• Algorithms1) Planning : Dynamic Programming Based2) Reinforcement Learning : Machine Learning Based
© 2016. SNU CSE Biointelligence Lab., http://bi.snu.ac.kr11
Polynomial Curve Fitting
Microsoft Excel 2007 의 추세선
© 2016. SNU CSE Biointelligence Lab., http://bi.snu.ac.kr13
Clustering
http://www.frankichamaki.com/data-driven-market-segmentation-more-effective-market-ing-to-segments-using-ai/
© 2016. SNU CSE Biointelligence Lab., http://bi.snu.ac.kr15
Videos• A crawling robot: a Q-learning examplehttps://www.youtube.com/watch?v=2iNrJx6IDEo
• Deep Reinforcement Learning for Robotic Ma-nipulation
https://youtu.be/ZhsEKTo7V04?t=1m27s