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Deep Reinforcement Learning

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코드

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

https://github.com/vita-epfl/CrowdNav

공식 코드

Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning

https://github.com/vita-epfl/DyNav

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Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning

https://github.com/vita-group/symbolicpcc

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Symbolic Distillation for Learned TCP Congestion Control

https://github.com/vittoriogiammarino/rl-for-unloading-from-pixels

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A Reinforcement Learning Approach for Robotic Unloading from Visual Observations

https://github.com/vkurenkov/language-grounding-multigoal

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Task-Oriented Language Grounding for Language Input with Multiple Sub-Goals of Non-Linear Order

https://github.com/vmicheli/delta-iris

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Efficient World Models with Context-Aware Tokenization

https://github.com/vwxyzjn/a2c_is_a_special_case_of_ppo

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A2C is a special case of PPO

https://github.com/vwxyzjn/cleanba

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Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform

https://github.com/vwxyzjn/cleanrl

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CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms

https://github.com/vwxyzjn/cleanrl/blob/master/cleanrl/rpo_continuous_action.py

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Robust Policy Optimization in Deep Reinforcement Learning

https://github.com/vwxyzjn/gym-microrts

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Comparing Observation and Action Representations for Deep Reinforcement Learning in $μ$RTS

https://github.com/vwxyzjn/gym-microrts-paper

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Gym-$μ$RTS: Toward Affordable Full Game Real-time Strategy Games Research with Deep Reinforcement Learning

https://github.com/vwxyzjn/invalid-action-masking

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A Closer Look at Invalid Action Masking in Policy Gradient Algorithms

https://github.com/wabbajack1/tapd

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Continual Deep Reinforcement Learning with Task-Agnostic Policy Distillation

https://github.com/walleclipse/reinforcement-learning-pulse-stacking

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An Optical Control Environment for Benchmarking Reinforcement Learning Algorithms

https://github.com/wan-zl/dt-drl

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Decision Theory-Guided Deep Reinforcement Learning for Fast Learning

https://github.com/wangjksjtu/rl-perturbed-reward

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Reinforcement Learning with Perturbed Rewards

https://github.com/wangyuhuix/TRGPPO

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Trust Region-Guided Proximal Policy Optimization

https://github.com/wangyuhuix/TRPPO

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Trust Region-Guided Proximal Policy Optimization

https://github.com/wangyuhuix/TrulyPPO

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Truly Proximal Policy Optimization

https://github.com/wassimtenachi/physo

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Deep symbolic regression for physics guided by units constraints: toward the automated discovery of physical laws

https://github.com/watermeloncq/drl-dynamic-optimization-portfolio-SB3py37

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A Deep Reinforcement Learning Framework for Dynamic Portfolio Optimization: Evidence from China's Stock Market

https://github.com/watermeloncq/drl-long-short-optimization-portfolio-SB3py37

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Deep Reinforcement Learning for Long-Short Portfolio Optimization

https://github.com/wdr123/darp-sbir

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Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval

https://github.com/weiwang-wys/irsconfigurationdrl

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Intelligent Reflecting Surface Configurations for Smart Radio Using Deep Reinforcement Learning

https://github.com/wh1992v/ggp-rl

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Assessing the Potential of Classical Q-learning in General Game Playing

https://github.com/wil3/gymfc

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Flight Controller Synthesis Via Deep Reinforcement Learning

https://github.com/wil3/neuroflight

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Flight Controller Synthesis Via Deep Reinforcement Learning

https://github.com/wildsky95/ZT-PFR

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Proactive and AoI-aware Failure Recovery for Stateful NFV-enabled Zero-Touch 6G Networks: Model-Free DRL Approach

https://github.com/wineslab/colosseum-oran-commag-dataset

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Intelligence and Learning in O-RAN for Data-driven NextG Cellular Networks

https://github.com/wleiiiii/gym-atc-attack-project

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Explainable and Safe Reinforcement Learning for Autonomous Air Mobility

https://github.com/wonjoon-yun/quantum-multi-agent-reinforcement-learning

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Quantum Multi-Agent Reinforcement Learning via Variational Quantum Circuit Design

https://github.com/wponghiran/lsm-rl

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Reinforcement Learning with Low-Complexity Liquid State Machines

https://github.com/wq13552463699/rrc_pos_ori

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Dexterous Robotic Manipulation using Deep Reinforcement Learning and Knowledge Transfer for Complex Sparse Reward-based Tasks

https://github.com/wrqccc/fjsp-drl

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Flexible Job Shop Scheduling via Dual Attention Network Based Reinforcement Learning

https://github.com/wulalago/AgentSPL

공식 코드

Agent with Warm Start and Adaptive Dynamic Termination for Plane Localization in 3D Ultrasound

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