Upgrade to Pro — share decks privately, control downloads, hide ads and more …

NeuralIPS

Avatar for Wonseok Jung Wonseok Jung
December 11, 2018
0
430

 NeuralIPS

Avatar for Wonseok Jung

Wonseok Jung

December 11, 2018
Tweet

More Decks by Wonseok Jung

See All by Wonseok Jung
Ai for business -self car driving
Avatar for Wonseok Jung wonseokjung
0
200
reinforcement_learning_.pdf
Avatar for Wonseok Jung wonseokjung
2
1.5k
원석이의 모두연에서 강화학습 보석되기
Avatar for Wonseok Jung wonseokjung
0
430
Introduction Deep Reinforcement Learning
Avatar for Wonseok Jung wonseokjung
0
160
Deep reinforcemenet learning -2
Avatar for Wonseok Jung wonseokjung
0
200
Deep Reinforcement Learning - Introduction
Avatar for Wonseok Jung wonseokjung
1
650
How to become a datascientist ?
Avatar for Wonseok Jung wonseokjung
2
2.3k
Review of Taylor series
Avatar for Wonseok Jung wonseokjung
1
120
꿈꾸는 Agent
Avatar for Wonseok Jung wonseokjung
2
150

Featured

See All Featured
Building the Perfect Custom Keyboard
Avatar for Naoto Takai takai
1
660
Raft: Consensus for Rubyists
Avatar for Patrick Van Stee vanstee
141
7.3k
Build your cross-platform service in a week with App Engine
Avatar for Jose L jlugia
234
18k
Dominate Local Search Results - an insider guide to GBP, reviews, and Local SEO
Avatar for Greg Gifford greggifford
PRO
0
23
The MySQL Ecosystem @ GitHub 2015
Avatar for Sam Lambert samlambert
251
13k
Navigating Team Friction
Avatar for Lara Hogan lara
191
16k
Measuring & Analyzing Core Web Vitals
Avatar for Philip Tellis bluesmoon
9
720
The Language of Interfaces
Avatar for Des Traynor destraynor
162
26k
Believing is Seeing
Avatar for Spiro Bolos oripsolob
0
17
Groundhog Day: Seeking Process in Gaming for Health
Avatar for Sebastian Deterding codingconduct
0
67
GraphQLの誤解/rethinking-graphql
Avatar for sonatard sonatard
74
11k
Visualizing Your Data: Incorporating Mongo into Loggly Infrastructure
Avatar for mongodb mongodb
48
9.8k

Transcript

  1. 3-JOWJUFEUBML/FVSBM*14 8POTFPL+VOH

  2. None
  3. None
  4. None

  5. 43࠙ীࢲ gradient descent methodۄҊ ೞ৓חؘ, gradient ascent੉׮. rewardܳ maximize ೞח

    policyܳ ଺ӝ ਤ೧ࢲח gradient aascent ׮.

  6. 43࠙ীࢲ gradient descent methodۄҊ ೞ৓חؘ, gradient ascent੉׮. rewardܳ maximize ೞח

    policyܳ ଺ӝ ਤ೧ࢲח gradient aascent ܳ ೧ঠೠ׮.
  7. None
  8. None
  9. None
  10. None
  11. None