📑

AI Paper Research

AI 논문 조사 및 정리

Foundations
강화학습Reinforcement Learning
Mastering Diverse Domains through World ...
Decision Transformer: Reinforcement Lear...
Mastering Atari, Go, Chess and Shogi by ...Grandmaster level in StarCraft II using ...
Soft Actor-Critic: Off-Policy Maximum En...
Proximal Policy Optimization AlgorithmsMastering Chess and Shogi by Self-Play w...
Mastering the game of Go with deep neura...Asynchronous Methods for Deep Reinforcem...
Playing Atari with Deep Reinforcement Le...
홈/강화학습/2019

강화학습 — 2019

2편의 논문

Nature 20203,000+

Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model

학습된 모델로 계획하여 Atari, 바둑, 체스, 장기 마스터하기

Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert et al. (2019)

Nature3,000+

Grandmaster level in StarCraft II using multi-agent reinforcement learning

다중 에이전트 강화학습을 이용한 스타크래프트 II 그랜드마스터 달성

Oriol Vinyals, Igor Babuschkin, et al. (2019)

← 강화학습 전체