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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/gaoyinfeng/piwm

공식 코드

Dream to Drive with Predictive Individual World Model

https://github.com/gaoyuankidult/PepperSocial

공식 코드

Learning Socially Appropriate Robot Approaching Behavior Toward Groups using Deep Reinforcement Learning

https://github.com/garyz712/drlpiddronecontrol

공식 코드

AirPilot: Interpretable PPO-based DRL Auto-Tuned Nonlinear PID Drone Controller for Robust Autonomous Flights

https://github.com/gauthamvasan/avg

공식 코드

Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers

https://github.com/gavlegoat/safe-learning

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Neurosymbolic Reinforcement Learning with Formally Verified Exploration

https://github.com/gd-goblin/NTU_DB_Data_Loader

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C-3PO: Cyclic-Three-Phase Optimization for Human-Robot Motion Retargeting based on Reinforcement Learning

https://github.com/geaps/geaps

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Goal Exploration Augmentation via Pre-trained Skills for Sparse-Reward Long-Horizon Goal-Conditioned Reinforcement Learning

https://github.com/gebob19/natural-policy-gradient-reinforcement-learning

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Understanding the Effects of Second-Order Approximations in Natural Policy Gradient Reinforcement Learning

https://github.com/geek-ai/MAgent

공식 코드

MAgent: A Many-Agent Reinforcement Learning Platform for Artificial Collective Intelligence

https://github.com/gemcollector/rl-vigen

공식 코드

RL-ViGen: A Reinforcement Learning Benchmark for Visual Generalization

https://github.com/gen-verse/cure

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Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning

https://github.com/geoffreyvd/deer-clean

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Component Transfer Learning for Deep RL Based on Abstract Representations

https://github.com/geraudnt/rosarl

공식 코드

ROSARL: Reward-Only Safe Reinforcement Learning

https://github.com/geraudnt/skill_machines

공식 코드

Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning

https://github.com/gfnorg/diffusion-finetuning

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Amortizing intractable inference in diffusion models for vision, language, and control

https://github.com/ggflow123/ddrl

공식 코드

Dataset Distillation for Offline Reinforcement Learning

https://github.com/ghimiremukesh/autonomous-driving

공식 코드

Lane Change Decision-Making through Deep Reinforcement Learning

https://github.com/ghliu/deepgsb

공식 코드

Deep Generalized Schrödinger Bridge

https://github.com/giangbang/strong-pareto-marl

공식 코드

Toward Finding Strong Pareto Optimal Policies in Multi-Agent Reinforcement Learning

https://github.com/giarcieri/robust-optimal-maintenance-planning-through-reinforcement-learning-and-rllib

공식 코드

POMDP inference and robust solution via deep reinforcement learning: An application to railway optimal maintenance

https://github.com/gilesluo/reassessdtr

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Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination

https://github.com/gilgameshd/grader

공식 코드

Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning

https://github.com/giorgioangel/myersoncoop

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Towards a more efficient computation of individual attribute and policy contribution for post-hoc explanation of cooperative multi-agent systems using Myerson values

https://github.com/giorgiograni/jssp_actor-critic_agasucci_monaci_grani

공식 코드

An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agents

https://github.com/giseung-park/blockseq

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Blockwise Sequential Model Learning for Partially Observable Reinforcement Learning

https://github.com/giseung-park/maxmin-morl

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The Max-Min Formulation of Multi-Objective Reinforcement Learning: From Theory to a Model-Free Algorithm

https://github.com/giuliapuntoit/RL-framework-iot

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RL-IoT: Reinforcement Learning to Interact with IoT Devices

https://github.com/giuse/DNE

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Playing Atari with Six Neurons

https://github.com/gjp1203/nui_in_madrl

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Negative Update Intervals in Deep Multi-Agent Reinforcement Learning

https://github.com/gkahn13/CAPs

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Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation

https://github.com/gkahn13/GtS

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Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight

https://github.com/gkahn13/LaND

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LaND: Learning to Navigate from Disengagements

https://github.com/gkahn13/gcg

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Self-supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation

https://github.com/gkswamy98/fast_irl

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Inverse Reinforcement Learning without Reinforcement Learning

https://github.com/gkthom/lagrseq

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LaGR-SEQ: Language-Guided Reinforcement Learning with Sample-Efficient Querying

https://github.com/glample/Arnold

공식 코드

Playing FPS Games with Deep Reinforcement Learning

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