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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/optimization-toolbox/DNE4py

Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

https://github.com/optimization-toolbox/deep-neuroevolution-mpi4py

Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

https://github.com/orrivlin/implicit-q-learning

Offline Reinforcement Learning with Implicit Q-Learning

https://github.com/oscarknagg/few-shot

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/osilab-kaist/smac_exp

The StarCraft Multi-Agent Challenge

https://github.com/osilab-kaist/smac_plus

The StarCraft Multi-Agent Challenge

https://github.com/osmr/imgclsmob

Progressive Neural Architecture Search

https://github.com/otoofim/ObjLocalisation

Active Object Localization with Deep Reinforcement Learning

https://github.com/oxquantum-repo/drl_for_quantum_measurement

Deep Reinforcement Learning for Efficient Measurement of Quantum Devices

https://github.com/oxwhirl/comix

FACMAC: Factored Multi-Agent Centralised Policy Gradients

https://github.com/oxwhirl/facmac

The StarCraft Multi-Agent Challenge

https://github.com/ozcell/gym_wmgds_ma

OpenAI Gym

https://github.com/p-casgrain/Nash-DQN

Deep Q-Learning for Nash Equilibria: Nash-DQN

https://github.com/p-morais/gym-cassie

DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills

https://github.com/pEAceATLast53/Social-Navigation

Robot Navigation in Constrained Pedestrian Environments using Reinforcement Learning

https://github.com/pablovin/MoodyFramework

The Chef's Hat Simulation Environment for Reinforcement-Learning-Based Agents

https://github.com/padlex/trl

Fine-Tuning Language Models from Human Preferences

https://github.com/paige-chang/Music-Recommendation-System

Deep Reinforcement Learning for List-wise Recommendations

https://github.com/paintception/Deep-Quality-Value-DQV-Learning-

Deep Quality-Value (DQV) Learning

https://github.com/paintception/Deep-Quality-Value-Family

Playing Atari with Deep Reinforcement Learning

https://github.com/pairlab/robosuite

Reinforcement and Imitation Learning for Diverse Visuomotor Skills

https://github.com/pairlab/v-cdn

Unsupervised Learning of Object Keypoints for Perception and Control

https://github.com/paperstiger/MoE-public

Discontinuity-Sensitive Optimal Control Learning by Mixture of Experts

https://github.com/para-zhou/RL_DDQ

Deep Dyna-Q: Integrating Planning for Task-Completion Dialogue Policy Learning

https://github.com/parilo/gym_bipedal_walker_v2_solution

A Distributional Perspective on Reinforcement Learning

https://github.com/parilo/rl-server

Playing Atari with Deep Reinforcement Learning

https://github.com/parnika31/MACAAC

Actor-Attention-Critic for Multi-Agent Reinforcement Learning

https://github.com/parthchadha/upsideDownRL

Training Agents using Upside-Down Reinforcement Learning

https://github.com/parthjaggi/flow

Flow: A Modular Learning Framework for Mixed Autonomy Traffic

https://github.com/pasrichashivam/Convnets_Grad-CAM_Grad-CAM-PlusPlus_Keras_tensorflow-2

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

https://github.com/pat-coady/trpo

High-Dimensional Continuous Control Using Generalized Advantage Estimation

https://github.com/pathway/alphaxos

Deep Reinforcement Learning with Double Q-learning

https://github.com/patniemeyer/ga-autoencoder

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

https://github.com/patrickhart/jaxdl

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/pauldaoudi/food

Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers

https://github.com/paulorauber/hpg

Hindsight policy gradients

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