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Policy Gradient Methods

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코드

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

https://github.com/tommyvsfu1/RL-NTU

Proximal Policy Optimization Algorithms

https://github.com/toni-sm/skrl

Trust Region Policy Optimization

https://github.com/tuanpnm99/RLPongAgent

Proximal Policy Optimization Algorithms

https://github.com/uber-common/deep-neuroevolution

Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents

https://github.com/ukyh/switch_disc_caption

Self-critical Sequence Training for Image Captioning

https://github.com/uvipen/super-mario-bros-ppo-pytorch

Proximal Policy Optimization Algorithms

https://github.com/vcadillog/PPO-Mario-Bros-Tensorflow-2

Proximal Policy Optimization Algorithms

https://github.com/vermashresth/damage-aware-PPO

Proximal Policy Optimization Algorithms

https://github.com/vheuthe/microbot_rl

Proximal Policy Optimization Algorithms

https://github.com/wangshub/RL-Stock

Proximal Policy Optimization Algorithms

https://github.com/wangyy161/DDPG_CNN_Pendulum_practice

Trust Region Policy Optimization

https://github.com/wangzhengfei0730/NIPS2018-AIforProsthetics

Proximal Policy Optimization Algorithms

https://github.com/wtliao/ImageTransformer

Self-critical Sequence Training for Image Captioning

https://github.com/xgfelicia/SRVRPG

Sample Efficient Policy Gradient Methods with Recursive Variance Reduction

https://github.com/xiaobai714/image_caption

Self-critical Sequence Training for Image Captioning

https://github.com/xiawenwen49/ppo

Proximal Policy Optimization Algorithms

https://github.com/xiuyu0000/new_papers_codes/tree/main/ppo

Proximal Policy Optimization Algorithms

https://github.com/xtma/simple-pytorch-rl

Proximal Policy Optimization Algorithms

https://github.com/yangpuPKU/L2SR-Learning-to-Sample-and-Reconstruct

Experimental design for MRI by greedy policy search

https://github.com/ylqi/gl-rg

Self-critical Sequence Training for Image Captioning

https://github.com/yoavalon/Quadcopter-env

Proximal Policy Optimization Algorithms

https://github.com/yoavalon/QuadcopterReinforcementLearning

Proximal Policy Optimization Algorithms

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/zjlab-ammi/llm4rl

Proximal Policy Optimization Algorithms

https://github.com/zsz-hst/RL_single_chase_point

Proximal Policy Optimization Algorithms

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.