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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/reinforcement-learning-kr/pg_travel

Proximal Policy Optimization Algorithms

https://github.com/reiniscimurs/TD3_Separate_Action

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/rejuvyesh/rllab

Benchmarking Deep Reinforcement Learning for Continuous Control

https://github.com/rekriz11/DeDiv

Complexity-Weighted Loss and Diverse Reranking for Sentence Simplification

https://github.com/remusionita/flow_rl

Flow: A Modular Learning Framework for Mixed Autonomy Traffic

https://github.com/renweiya/RFQ-RFAC-Represented-Value-Function-Approach-for-Large-Scale-Multi-Agent-Reinforcement-Learning

Represented Value Function Approach for Large Scale Multi Agent Reinforcement Learning

https://github.com/reservoirpy/reservoirpy

Evolving Reservoirs for Meta Reinforcement Learning

https://github.com/rgilman33/carlita

Leveraging Procedural Generation to Benchmark Reinforcement Learning

https://github.com/rgreenblatt/ai_alignment_readings

Cooperative Inverse Reinforcement Learning

https://github.com/richard-UMD/Unity-ml-agents

Unity: A General Platform for Intelligent Agents

https://github.com/richardehughes/chnflow

Flow: A Modular Learning Framework for Mixed Autonomy Traffic

https://github.com/richardrl/cartpole-request-for-research

Benchmarking Deep Reinforcement Learning for Continuous Control

https://github.com/richardrl/rlkit-relational

Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning

https://github.com/richemslie/galvanise_zero

Thinking Fast and Slow with Deep Learning and Tree Search

https://github.com/rickyegl/BeyondTheRainbowICLR

Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC

https://github.com/rickyegl/BeyondTheRainbowM

Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC

https://github.com/riflezhang/llava-hound-dpo

Improve Vision Language Model Chain-of-thought Reasoning

https://github.com/rigetti/gym-forest

Automated quantum programming via reinforcement learning for combinatorial optimization

https://github.com/rikluost/RL_DQN_Pong

Playing Atari with Deep Reinforcement Learning

https://github.com/rishabhsahrawat/textbasedgameusingNeuralNet

Language Understanding for Text-based Games Using Deep Reinforcement Learning

https://github.com/rishavb123/MineRL

Playing Atari with Deep Reinforcement Learning

https://github.com/riveSunder/harli_learning

Meta-Learning through Hebbian Plasticity in Random Networks

https://github.com/riveSunder/moving_in_morley

Exploration by Random Network Distillation

https://github.com/rk1998/robot-sac

Continuous control with deep reinforcement learning

https://github.com/rle-foundation/hsuanwu

RLLTE: Long-Term Evolution Project of Reinforcement Learning

https://github.com/rll-research/rune

Reward Uncertainty for Exploration in Preference-based Reinforcement Learning

https://github.com/rll/rllab

Benchmarking Deep Reinforcement Learning for Continuous Control

https://github.com/rlworkgroup/garage

Benchmarking Deep Reinforcement Learning for Continuous Control

https://github.com/rmrafailov/lompo

Offline Reinforcement Learning from Images with Latent Space Models

https://github.com/robbiejones96/RubiksSolver

Solving the Rubik's Cube Without Human Knowledge

https://github.com/robintyh1/icml2021-pengqlambda

Safe and Efficient Off-Policy Reinforcement Learning

https://github.com/robinzixuan/IQN_Agent

Distributional Reinforcement Learning with Quantile Regression

https://github.com/roboticist-by-day/Rainbow_DQN

Rainbow: Combining Improvements in Deep Reinforcement Learning

https://github.com/rocksat/PatchDrop

Learning When and Where to Zoom with Deep Reinforcement Learning

https://github.com/rohit129/Movie_KnowledgeGraph_QA

Dialogue Learning With Human-In-The-Loop

https://github.com/rohithreddy024/Text-Summarizer-Pytorch

A Deep Reinforced Model for Abstractive Summarization

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