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Policy Gradient Methods

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코드

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

https://github.com/tud-amr/parl

공식 코드

Predictable Reinforcement Learning Dynamics through Entropy Rate Minimization

https://github.com/uber-research/deep-neuroevolution

공식 코드

Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents

https://github.com/ubiquition/drl

공식 코드

Partial advantage estimator for proximal policy optimization

https://github.com/venktesh22/ExpressLanes_Deep-RL

공식 코드

Deep Reinforcement Learning Algorithm for Dynamic Pricing of Express Lanes with Multiple Access Locations

https://github.com/wujiduan/zero-sum-lq-games

공식 코드

Learning Zero-Sum Linear Quadratic Games with Improved Sample Complexity and Last-Iterate Convergence

https://github.com/xylee95/md-pgt

공식 코드

MDPGT: Momentum-based Decentralized Policy Gradient Tracking

https://github.com/yuyq18/steptool

공식 코드

StepTool: A Step-grained Reinforcement Learning Framework for Tool Learning in LLMs

https://bitbucket.org/act-lab/release

Proximal Policy Optimization Algorithms

https://github.com/170928/-Review-Generative-Adversarial-Imitation-Learning

Trust Region Policy Optimization

https://github.com/170928/-Review-Proximal-Policy-Optimization-Algorithms

Proximal Policy Optimization Algorithms

https://github.com/18jeffreyma/cgd_scratch_work

Competitive Policy Optimization

https://github.com/18jeffreyma/multi_cmd

Competitive Policy Optimization

https://github.com/2mawi2/master-thesis-experiments

Proximal Policy Optimization Algorithms

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

Proximal Policy Optimization Algorithms

https://github.com/Aravind-11/AI-Gaming

Proximal Policy Optimization Algorithms

https://github.com/Aravind-11/IITM_Saastra

Proximal Policy Optimization Algorithms

https://github.com/Aravind-11/Multi-Agent-RL

Proximal Policy Optimization Algorithms

https://github.com/BIT-aerial-robotics/AquaML/blob/2.1.11/AquaML/rlalgo/COPGAgent.py

Clipped-Objective Policy Gradients for Pessimistic Policy Optimization

https://github.com/BIT-aerial-robotics/AquaML/blob/2.1.11/AquaML/rlalgo/PPOAgent.py

Proximal Policy Optimization Algorithms

https://github.com/BerkeleyLearnVerify/VerifAI

Proximal Policy Optimization Algorithms

https://github.com/BrianPulfer/PapersReimplementations

Proximal Policy Optimization Algorithms

https://github.com/CSautier/Breakout

Proximal Policy Optimization Algorithms

https://github.com/CSautier/PongBot

Proximal Policy Optimization Algorithms

https://github.com/Crevass/Hybrid-Agent

Proximal Policy Optimization Algorithms

https://github.com/DLR-RM/stable-baselines3

Trust Region Policy Optimization

https://github.com/DMIU-ShELL/MOSAIC

Proximal Policy Optimization Algorithms

https://github.com/DartML/PPO-Stein-Control-Variate

Action-depedent Control Variates for Policy Optimization via Stein's Identity

https://github.com/DavidCastilloAlvarado/Path-planning-and-Reinforcement-Learning

Proximal Policy Optimization Algorithms

https://github.com/DeepGraphLearning/RecommenderSystems

Ekar: An Explainable Method for Knowledge Aware Recommendation

https://github.com/DevSlem/AINE-DRL

Proximal Policy Optimization Algorithms

https://github.com/Dlut-lab-zmn/Image-Captioning-Attack

Self-critical Sequence Training for Image Captioning

https://github.com/EconomistGrant/HTFE-tensortrade

Proximal Policy Optimization Algorithms

https://github.com/FJSam/SelfCritical_ImageCaptioning

Self-critical Sequence Training for Image Captioning

https://github.com/FMArduini/python-rl

Proximal Policy Optimization Algorithms

https://github.com/GiadaSimionato/Reasoning_Agents_2020

Proximal Policy Optimization Algorithms

https://github.com/Giovanni3A/LearningDynamics

Neural Replicator Dynamics

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.