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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/acutronicrobotics/ros2learn

ROS2Learn: a reinforcement learning framework for ROS 2

https://github.com/acyclics/MPO

Maximum a Posteriori Policy Optimisation

https://github.com/adammenges/DARTS-PyTorch

DARTS: Differentiable Architecture Search

https://github.com/adamos581/ppo-keras-football

Proximal Policy Optimization Algorithms

https://github.com/addy369/AnimalAI

Unity: A General Platform for Intelligent Agents

https://github.com/adieyal/sd-dynamic-prompts

Optimizing Prompts for Text-to-Image Generation

https://github.com/adik993/ppo-pytorch

High-Dimensional Continuous Control Using Generalized Advantage Estimation

https://github.com/adityabingi/Dreamer

Dream to Control: Learning Behaviors by Latent Imagination

https://github.com/adityagilra/archibrain

Multi-timescale memory dynamics in a reinforcement learning network with attention-gated memory

https://github.com/aduerig/burrus

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

https://github.com/adymaharana/DeepPath_PyTorch

DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning

https://github.com/aerialroboticsgroup/agile-tethered-perching

Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control

https://github.com/afengisme11/IAM-Reproduce

Influence-aware Memory Architectures for Deep Reinforcement Learning

https://github.com/afrakilic/btn-kernel-machines

Reinforcement Learning-based Model Predictive Control for Greenhouse Climate Control

https://github.com/agent-rl/research

ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning

https://github.com/agentica-project/verl-pipeline

Enhancing Multi-Step Reasoning Abilities of Language Models through Direct Q-Function Optimization

https://github.com/agiachris/STAP

Dream to Control: Learning Behaviors by Latent Imagination

https://github.com/agnesdeng/misle

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

https://github.com/ahefnycmu/rpsp

Recurrent Predictive State Policy Networks

https://github.com/ahundt/sharpDARTS

DARTS: Differentiable Architecture Search

https://github.com/ai-nikolai/bsuite

Behaviour Suite for Reinforcement Learning

https://github.com/ai-winter/python_motion_planning

Continuous control with deep reinforcement learning

https://github.com/aigerimb/FFEVSS

A Reinforcement Learning Approach for Rebalancing Electric Vehicle Sharing Systems

https://github.com/ailab-pku/rl-framework

Continuous control with deep reinforcement learning

https://github.com/ailabdsunipi/pymarlzooplus

The StarCraft Multi-Agent Challenge

https://github.com/aimagelab/mammoth

Progressive Neural Networks

https://github.com/aithlab/ImprovingGate

Improving the Gating Mechanism of Recurrent Neural Networks

https://github.com/ajaykrishnan23/Grad_Cam

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

https://github.com/ajayn1997/RL-VRP-PtrNtwrk

Reinforcement Learning for Solving the Vehicle Routing Problem

https://github.com/ajaysub110/rl-pytorch

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

https://github.com/akanazawa/motion_reconstruction

SFV: Reinforcement Learning of Physical Skills from Videos

https://github.com/akanimax/Variational_Discriminator_Bottleneck

Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow

https://github.com/akashsonowal/ddpo-pytorch

Training Diffusion Models with Reinforcement Learning

https://github.com/aksub99/MolDQN-pytorch

Optimization of Molecules via Deep Reinforcement Learning

https://github.com/akterskii/rlpyt

Accelerated Methods for Deep Reinforcement Learning

https://github.com/alaalab/webcp

A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

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