Papers with Code 아카이브

Deep Reinforcement Learning

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 0
보존된 평가 기록: 0

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/zhanghainan/RNN-S2S

Deep Reinforcement Learning for Dialogue Generation

https://github.com/zhanghainan/RNN-encdec

Deep Reinforcement Learning for Dialogue Generation

https://github.com/zhanghainan/ReinforcingCoherence

Deep Reinforcement Learning for Dialogue Generation

https://github.com/zhanghainan/TailoredSeq2Seq2DifferentConversationScenarios

Deep Reinforcement Learning for Dialogue Generation

https://github.com/zhanghainan/s2s-with-attention

Deep Reinforcement Learning for Dialogue Generation

https://github.com/zhengant/dqn_reversi

Deep Reinforcement Learning with Double Q-learning

https://github.com/zhuliwen/pku_traffic_lights

MetaVIM: Meta Variationally Intrinsic Motivated Reinforcement Learning for Decentralized Traffic Signal Control

https://github.com/zilongzheng/visdial-gnn

Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning

https://github.com/zlr20/saferl_kit

Learning to Walk in the Real World with Minimal Human Effort

https://github.com/zoeyuchao/MPE-pytorch

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/zoeyuchao/MPEnew-pytorch

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/zoli333/Weight-Normalization

Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks

https://github.com/zowiezhang/stas

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/zuoxingdong/VIN_PyTorch_Visdom

Neural Map: Structured Memory for Deep Reinforcement Learning

https://github.com/zynk13/dueling-dqn-Reinforcement-learning

Dueling Network Architectures for Deep Reinforcement Learning

https://github.com/zzmtsvv/rl_task

Extreme Q-Learning: MaxEnt RL without Entropy

https://github.com/zzmtsvv/sac_drnd

Exploration and Anti-Exploration with Distributional Random Network Distillation

https://gitlab.com/stchrist/ViscousThreads

Remember and Forget for Experience Replay

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.