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Distributional Reinforcement Learning
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Value distribution is the distribution of the random return received by a reinforcement learning agent. it been used for a specific purpose such as implementing risk-aware behaviour.
We have random return Z whose expectation is the value Q. This random return is also described by a recursive equation, but one of a distributional nature
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zpschang/MD3QN
공식 코드Distributional Reinforcement Learning for Multi-Dimensional Reward Functions
https://github.com/ACampero/dopamine
Implicit Quantile Networks for Distributional Reinforcement Learning
https://github.com/Abdelhamid-bouzid/Distributional-RL
Distributional Reinforcement Learning with Quantile Regression
https://github.com/BY571/FQF-and-Extensions
Fully Parameterized Quantile Function for Distributional Reinforcement Learning
https://github.com/BY571/IQN
Implicit Quantile Networks for Distributional Reinforcement Learning
https://github.com/DLR-RM/stable-baselines3
Distributional Reinforcement Learning with Quantile Regression
https://github.com/GoingMyWay/dopamine_reward_decomposition
Implicit Quantile Networks for Distributional Reinforcement Learning
https://github.com/KatyNTsachi/Hierarchical-RL
Implicit Quantile Networks for Distributional Reinforcement Learning
https://github.com/Kchu/DeepRL_CK
Distributional Reinforcement Learning with Quantile Regression
https://github.com/SeungeonBaek/continuous-agents-test
https://github.com/SeungeonBaek/discrete-agents-test
Distributional Reinforcement Learning with Quantile Regression
https://github.com/V0LsTeR/DQN_heap
Implicit Quantile Networks for Distributional Reinforcement Learning
https://github.com/V0LsTeR/dopamine_prioritized_buffer
Implicit Quantile Networks for Distributional Reinforcement Learning
https://github.com/ZiyiLiubird/DeepMARL-PyTorch
Distributional Reinforcement Learning with Quantile Regression
https://github.com/ars-ashuha/quantile-regression-dqn-pytorch
Distributional Reinforcement Learning with Quantile Regression
https://github.com/chainer/chainerrl
Implicit Quantile Networks for Distributional Reinforcement Learning
https://github.com/daggertye/GAN-Q-Learning
https://github.com/facebookresearch/Horizon
Distributional Reinforcement Learning with Quantile Regression
https://github.com/facebookresearch/ReAgent
Distributional Reinforcement Learning with Quantile Regression
https://github.com/ku2482/fqf-iqn-qrdqn.pytorch
Distributional Reinforcement Learning with Quantile Regression
https://github.com/ku2482/rljax
Distributional Reinforcement Learning with Quantile Regression
https://github.com/marload/DistRL-TensorFlow2
Distributional Reinforcement Learning with Quantile Regression
https://github.com/marload/dist-rl-tf2
Distributional Reinforcement Learning with Quantile Regression
https://github.com/microsoft/FQF
Fully Parameterized Quantile Function for Distributional Reinforcement Learning
https://github.com/opendilab/DI-engine
Fully Parameterized Quantile Function for Distributional Reinforcement Learning
https://github.com/opendilab/DI-engine/blob/main/ding/policy/iqn.py
Implicit Quantile Networks for Distributional Reinforcement Learning
https://github.com/opendilab/DI-engine/blob/main/ding/policy/qrdqn.py
Distributional Reinforcement Learning with Quantile Regression
https://github.com/pihey1995/DistributionalRL
Implicit Quantile Networks for Distributional Reinforcement Learning
https://github.com/sannebh/riskaverse
Distributional Reinforcement Learning with Quantile Regression
https://github.com/sannebh/riskaverse_rl
Distributional Reinforcement Learning with Quantile Regression
https://github.com/senya-ashukha/quantile-regression-dqn-pytorch
Distributional Reinforcement Learning with Quantile Regression
https://github.com/sjYoondeltar/IQN_example
Implicit Quantile Networks for Distributional Reinforcement Learning
https://github.com/sjYoondeltar/myRL_example
Implicit Quantile Networks for Distributional Reinforcement Learning
https://github.com/uncharted-technologies/risk-and-uncertainty
Estimating Risk and Uncertainty in Deep Reinforcement Learning
https://github.com/yuguangyue/Implicit_Distributional_RL
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.