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Reinforcement Learning (RL)

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Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

코드

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

https://github.com/zefang-liu/group-recommender

공식 코드

Deep Reinforcement Learning based Group Recommender System

https://github.com/zengyi-qin/bcbf

공식 코드

SABLAS: Learning Safe Control for Black-box Dynamical Systems

https://github.com/zero-coder/fecam

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Enhancing data efficiency in reinforcement learning: a novel imagination mechanism based on mesh information propagation

https://github.com/zeroxleo/ml-agent

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ML-Agent: Reinforcing LLM Agents for Autonomous Machine Learning Engineering

https://github.com/zeyubian/2feope

공식 코드

Off-policy Evaluation in Doubly Inhomogeneous Environments

https://github.com/zeyuzhang1901/unified-off-policy-ltr-neurips2023

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Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective

https://github.com/zgong11/TraC

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Offline Safe Reinforcement Learning Using Trajectory Classification

https://github.com/zhang-zengjie/code_2023_iecon_shaping_wu

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Risk-Aware Reward Shaping of Reinforcement Learning Agents for Autonomous Driving

https://github.com/zhangquanchen/visrl

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VisRL: Intention-Driven Visual Perception via Reinforced Reasoning

https://github.com/zhangry868/S2VGD

공식 코드

Learning Structural Weight Uncertainty for Sequential Decision-Making

https://github.com/zhangzizhen/ml-dam

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Meta-Learning-Based Deep Reinforcement Learning for Multiobjective Optimization Problems

https://github.com/zhanzxy5/MOPP

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Model-Based Offline Planning with Trajectory Pruning

https://github.com/zhao-song/Softmax-DQN

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Revisiting the Softmax Bellman Operator: New Benefits and New Perspective

https://github.com/zhaochen0110/openthinkimg

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OpenThinkIMG: Learning to Think with Images via Visual Tool Reinforcement Learning

https://github.com/zhaolingao/rebel

공식 코드

REBEL: Reinforcement Learning via Regressing Relative Rewards

https://github.com/zhaoyi11/adaptive_bc

공식 코드

Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning

https://github.com/zhehui-huang/quad-swarm-rl

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QuadSwarm: A Modular Multi-Quadrotor Simulator for Deep Reinforcement Learning with Direct Thrust Control

https://github.com/zhejz/carla-roach

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End-to-End Urban Driving by Imitating a Reinforcement Learning Coach

https://github.com/zhendong-wang/diffusion-policies-for-offline-rl

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Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning

https://github.com/zhenduow/conversationalQA

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Controlling the Risk of Conversational Search via Reinforcement Learning

https://github.com/zheng0428/more_

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MORE-3S:Multimodal-based Offline Reinforcement Learning with Shared Semantic Spaces

https://github.com/zheng321/deep-reinforcement-learning-for-cost-effective-medical-diagnosis

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Deep Reinforcement Learning for Cost-Effective Medical Diagnosis

https://github.com/zhenghuazx/BayesianLRPolicySearch

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Green Simulation Assisted Reinforcement Learning with Model Risk for Biomanufacturing Learning and Control

https://github.com/zhenghuazx/EHR-RL

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Personalized Multimorbidity Management for Patients with Type 2 Diabetes Using Reinforcement Learning of Electronic Health Records

https://github.com/zhenghuazx/vrer_policy_gradient

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Variance Reduction based Experience Replay for Policy Optimization

https://github.com/zhengyinan-air/omiga

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Offline Multi-Agent Reinforcement Learning with Implicit Global-to-Local Value Regularization

https://github.com/zhentingwang/dump

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DUMP: Automated Distribution-Level Curriculum Learning for RL-based LLM Post-training

https://github.com/zhihanyang2022/off-policy-continuous-control

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Recurrent Off-policy Baselines for Memory-based Continuous Control

https://github.com/zhimengj0326/ekRLB

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Adaptive Risk-Aware Bidding with Budget Constraint in Display Advertising

https://github.com/zhiqiangzhongddu/PM-HGNN

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Personalised Meta-path Generation for Heterogeneous GNNs

https://github.com/zhiyuanhubj/meta-ability-alignment

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Beyond 'Aha!': Toward Systematic Meta-Abilities Alignment in Large Reasoning Models

https://github.com/zhongxiayan/mixed_autonomy_intersections

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Reinforcement Learning for Mixed Autonomy Intersections

https://github.com/zhougroup/IDAC

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Implicit Distributional Reinforcement Learning

https://github.com/zhourunlong/RL-for-Combinatorial-Optimization

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Understanding Curriculum Learning in Policy Optimization for Online Combinatorial Optimization

https://github.com/zhourunlong/reflect-rl

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Reflect-RL: Two-Player Online RL Fine-Tuning for LMs

https://github.com/zhouzypaul/wsrl

공식 코드

Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data

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