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Atari Games

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평가표: 65
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The Atari 2600 Games task (and dataset) involves training an agent to achieve high game scores.

<span style="color:grey; opacity: 0.6">( Image credit: Playing Atari with Deep Reinforcement Learning )</span>

코드

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

https://github.com/sannebh/riskaverse_rl

Distributional Reinforcement Learning with Quantile Regression

https://github.com/sarahisyoung/rlpyt

Accelerated Methods for Deep Reinforcement Learning

https://github.com/saschaschramm/Pong

Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation

https://github.com/sauxpa/ML_101

Temporal Regularization in Markov Decision Process

https://github.com/seacevedo/ReinforcementLearningProjects

Deep Reinforcement Learning with Double Q-learning

https://github.com/self-supervisor/how_to_stay_curious_while_avoiding_noisy_tvs

Large-Scale Study of Curiosity-Driven Learning

https://github.com/senya-ashukha/quantile-regression-dqn-pytorch

Distributional Reinforcement Learning with Quantile Regression

https://github.com/seolhokim/DistributedRL-Pytorch-Ray

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

https://github.com/seolhokim/SimpleDistributedRL

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

https://github.com/seungjaeryanlee/combined-experience-replay

A Deeper Look at Experience Replay

https://github.com/seungjaeryanlee/rldb

Noisy Networks for Exploration

https://github.com/shakti365/nes

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

https://github.com/shaneallcroft/SSB64RLBot

Beating the World's Best at Super Smash Bros. with Deep Reinforcement Learning

https://github.com/sharan-dce/A3C

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/shashwatsaxena571/DRL-navigation

Deep Reinforcement Learning with Double Q-learning

https://github.com/shehrum/RL_Navigation

Deep Reinforcement Learning with Double Q-learning

https://github.com/sherry4186/Distributed-DQN

Distributed Prioritized Experience Replay

https://github.com/shivamsaboo17/overcoming-catastrophic-forgetting-in-neural-networks

Overcoming catastrophic forgetting in neural networks

https://github.com/shuli0808/DQN

A Distributional Perspective on Reinforcement Learning

https://github.com/silvialuu/DRL-2018

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

https://github.com/sirdr/TRPO.jl

Trust Region Policy Optimization

https://github.com/sisl/event-driven-rllab

Benchmarking Deep Reinforcement Learning for Continuous Control

https://github.com/sisl/gail-driver

Benchmarking Deep Reinforcement Learning for Continuous Control

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/smj007/Breakout_A3C

Playing Atari Games with Deep Reinforcement Learning and Human Checkpoint Replay

https://github.com/snhwang/p1_navigation_SNH

Prioritized Experience Replay

https://github.com/snhwang/p2-continuous-control-SNH

Prioritized Experience Replay

https://github.com/snhwang/p3_collab-compet

Prioritized Experience Replay

https://github.com/snjstudent/MyMuzero

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

https://github.com/sourenaKhanzadeh/snakeAi

Playing Atari with Deep Reinforcement Learning

https://github.com/spideralessio/TRPO-Tensorflow2

Trust Region Policy Optimization

https://github.com/spragunr/deep_q_rl

Playing Atari with Deep Reinforcement Learning

https://github.com/srvCodes/continual-learning-benchmark

Overcoming catastrophic forgetting in neural networks

https://github.com/ssainz/reinforcement_learning_algorithms

Deep Reinforcement Learning with Double Q-learning

https://github.com/ssg-research/flare

Characterizing Attacks on Deep Reinforcement Learning

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