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Reinforcement Learning

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코드

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

https://github.com/google-research/tiny-differentiable-simulator

Interactive Differentiable Simulation

https://github.com/google/active-qa

Ask the Right Questions: Active Question Reformulation with Reinforcement Learning

https://github.com/google/brain-tokyo-workshop

Learning to Predict Without Looking Ahead: World Models Without Forward Prediction

https://github.com/google/brain-tokyo-workshop/tree/master/WANNRelease

Weight Agnostic Neural Networks

https://github.com/google/evojax

Simple random search provides a competitive approach to reinforcement learning

https://github.com/google/maddpg-replication

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

https://github.com/google/t5patches

Fine-Tuning Language Models from Human Preferences

https://github.com/google/trax

Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

https://github.com/goolulusaurs/WorldModels

Gotta Learn Fast: A New Benchmark for Generalization in RL

https://github.com/gordicaleksa/pytorch-learn-reinforcement-learning

Playing Atari with Deep Reinforcement Learning

https://github.com/gorosgobe/dsae-torch

Deep Spatial Autoencoders for Visuomotor Learning

https://github.com/gouxiangchen/dueling-DQN-pytorch

Dueling Network Architectures for Deep Reinforcement Learning

https://github.com/gowriaddepalli/ML_DL_Research_collab_base

Deep Reinforcement Learning framework for Autonomous Driving

https://github.com/grananqvist/reinforcement-learning-super-mario-A3C

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/grass123-hub/DQN

Playing Atari with Deep Reinforcement Learning

https://github.com/grayswanai/nanogcg

An Alternative Softmax Operator for Reinforcement Learning

https://github.com/grtzsohalf/SpeechNet-codebase

Gradient Surgery for Multi-Task Learning

https://github.com/grtzsohalf/pt.darts

DARTS: Differentiable Architecture Search

https://github.com/gshashank84/CheXNet

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/gstoica27/cpg_ppo

Proximal Policy Optimization Algorithms

https://github.com/gt-coar/Q-Learning-LFA

Finite-Sample Analysis of Nonlinear Stochastic Approximation with Applications in Reinforcement Learning

https://github.com/gtagency/beta-zero

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

https://github.com/gtegner/hyper-gan

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

https://github.com/gtrll/dartenv

OpenAI Gym

https://github.com/guanton/umfi_python

Information-Theoretic State Variable Selection for Reinforcement Learning

https://github.com/guardianzc/discopen-medbox-dialodiagnosis

Hierarchical Reinforcement Learning for Automatic Disease Diagnosis

https://github.com/guicho271828/latplan-fosae

Unsupervised Grounding of Plannable First-Order Logic Representation from Images

https://github.com/guillaumeboniface/bananaland

Deep Reinforcement Learning with Double Q-learning

https://github.com/guillaumeboniface/reacher

High-Dimensional Continuous Control Using Generalized Advantage Estimation

https://github.com/gungui98/deeprl-a3c-ai2thor

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/gunjan99/Review-of-World-Models-using-Latex

World Models

https://github.com/guofeng201507/ISA-IPA-2020-05-05-IS1PT-GRP-High5-StockTrading

Proximal Policy Optimization Algorithms

https://github.com/guojm14/HVF

Hindsight Value Function for Variance Reduction in Stochastic Dynamic Environment

https://github.com/guoyongcs/NATv2

DARTS: Differentiable Architecture Search

https://github.com/gustavokcouto/hgail

End-to-End Urban Driving by Imitating a Reinforcement Learning Coach

https://github.com/gwthomas/gtml

Continuous control with deep reinforcement learning

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