| Year | Venue | Model | Title | Algorithm | Paper | Code |
|---|---|---|---|---|---|---|
| 2018 | ACM SIGKDD | GAM | Graph Classification using structural attention | Partially Observable Markov Decision Process (POMDP) | Paper | \ |
| 2019 | IEEE TNSM | DDPG-HFA | A Deep Reinforcement Learning Approach for VNF Forwarding Graph Embedding | DDPG | Paper | \ |
| 2019 | arXiv | GraphNAS | GraphNAS: Graph Neural Architecture Search with Reinforcement Learning | MDP | Paper | Code |
| 2019 | arXiv | AGNN | Auto-GNN: Neural Architecture Search of Graph Neural Networks | REINFORCE | Paper | \ |
| 2019 | AISTATS | GRPI | Representation Learning on Graphs: A Reinforcement Learning Application | MDP | Paper | Code |
| 2019 | ICDM | GDPNet | Learning Robust Representations with Graph Denoising Policy Network | MDP | Paper | \ |
| 2020 | ICPR | DAGCN | Reinforcement learning with dual attention guided graph convolution for relation extraction | MDP | Paper | \ |
| 2020 | IEEE J-SAC | A3C+GCN | Automatic Virtual Network Embedding: A Deep Reinforcement Learning Approach With Graph Convolutional Networks | A3C | Paper | \ |
| 2020 | ICPR | DAGCN | Reinforcement learning with dual attention guided graph convolution for relation extraction | MDP | Paper | \ |
| 2020 | ICASSP | RLNet | Learning network representation through reinforcement learning | MDP | Paper | \ |
| 2020 | NeurIPS | GPA | Graph Policy Network for Transferable Active Learning on Graphs | MDP | Paper | Code |
| 2020 | KDD | Policy-GNN | Policy-GNN: Aggregation Optimization for Graph Neural Networks | DQN | Paper | Code |
| 2020 | ICLR | DGN | Graph Convolutional Reinforcement Learning | Q-Learning | Paper | Code |
| 2020 | AAAI/ACMAI | GAEA | GAEA: Graph Augmentation for Equitable Access via Reinforcement Learning | MDP | Paper | Code |
| 2021 | DASFAA | IMGER | A reinforcement learning model for influence maximization in social networks | DDQN | Paper | \ |
| 2021 | IEEE ICDM | GQNAS | GQNAS: Graph Q Network for Neural Architecture Search | DQN | Paper | \ |
| 2021 | IEEE TKDE | Netrl | Netrl: Task-aware network denoising via deep reinforcement learning | DQN | Paper | Code |
| 2021 | IEEE ICDM | ACE-HGNN | ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network | Nash Q-leaning | Paper | \ |
| 2021 | WWW | SUGAR | SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism | Q-Learning | Paper | Code |
| 2021 | ACM TOIS | RioGNN | Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks | MDP | Paper | Code |
| 2022 | Knowledge-Based Systems | AFGSL | AFGSL: Automatic Feature Generation based on Graph Structure Learning | Q-Learning | Paper | \ |
| 2022 | arXiv | GraphAug | Automated Data Augmentations for Graph Classification | MDP | Paper | \ |
| 2022 | IEEE TKDE | RTGNN | Multi-view Tensor Graph Neural Networks Through Reinforced Aggregation | MDP | Paper | Code |
| 2022 | Neurocomputing | Treeago | Treeago: Tree-structure aggregation and optimization for graph neural network | DQN | Paper | \ |
| 2022 | IEEE TKDE | GraphNAS++ | GraphNAS++: Distributed Architecture Search for Graph Neural Networks | REINFORCE | Paper | \ |
| 2022 | Neural Computing and Applications | Kyriakides et al. | Evolving graph convolutional networks for neural architecture search | MDP | Paper | \ |
| 2022 | Information Sciences | GraphTUL | Contextual spatio-temporal graph representation learning for reinforced human mobility mining | MDP | Paper | \ |
| 2022 | AAAI | BiGeNe | Batch Active Learning with Graph Neural Networks via Multi-Agent Deep Reinforcement Learning | DQN | Paper | \ |
| 2022 | arXiv | AdaNet | Robust Knowledge Adaptation for Dynamic Graph Neural Networks | REINFORCE | Paper | \ |
| 2022 | Annals of Operations Research | CRL | Counterfactual based reinforcement learning for graph neural networks | MolDQN | Paper | \ |
| 2023 | ICML | DeepIM | Deep Graph Representation Learning and Optimization for Influence Maximization | MDP | Paper | Code |
| 2023 | IEEE TKDE | HGNAS++: | Efficient Architecture Search for Heterogeneous Graph Neural Networks | MDP | Paper | \ |
| 2023 | Information Sciences | DeepGNAS | Search for deep graph neural networks | DQN | Paper | \ |
| 2023 | MLSys | X-RLflow | X-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation | PPO | Paper | Code |
| Year | Venue | Model | Title | Algorithm | Paper | Code |
|---|---|---|---|---|---|---|
| 2018 | ICML | RL-S2V | Adversarial Attack on Graph Structured Data | Q-learning | Paper | \ |
| 2018 | TrustCom/BigDataSE | Yousefi et al. | A Reinforcement Learning Approach for Attack Graph Analysis | Q-learning | Paper | \ |
| 2019 | arXiv | ReWatt | Attacking Graph Convolutional Networks via Rewiring | MDP | Paper | \ |
| 2020 | CIKM | CARE-GNN | Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters | BMAB | Paper | Code |
| 2020 | WWW | NIPA | Adversarial Attacks on Graph Neural Networks via Node Injections: A Hierarchical Reinforcement Learning Approach | DQN | Paper | \ |
| 2021 | SBP-BRiMS | Dineen et al. | Reinforcement Learning for Data Poisoning on Graph Neural Networks | REINFORCE | Paper | \ |
| 2022 | Neural Computing and Applications | Wu et al. | Poisoning attacks against knowledge graph-based recommendation systems using deep reinforcement learning | MDP | Paper | \ |
| 2022 | KDD | KGAttack | Knowledge-enhanced Black-box Attacks for Recommendations | AC | Paper | \ |
| 2022 | IEEE TKDE | RL-GraphMI | Model Inversion Attacks Against Graph Neural Networks | Q-Learning | Paper | Code |
| 2023 | IJCNN | AdRumor-RL | Interpretable and Effective Reinforcement Learning for Attacking against Graph-based Rumor Detection | MDP | Paper | \ |
| 2024 | IEEE Transactions on Computational Social Systems | G2-SNIA | Single-Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learning | PPO | Paper | Code |
| 2024 | Neural Networks | HRBBA | Black-box attacks on dynamic graphs via adversarial topology perturbations | DDPG | Paper | \ |
| 2024 | IEEE Transactions on Computational Social Systems | Det-H/R | Detecting Targets of Graph Adversarial Attacks With Edge and Feature Perturbations | DQN | Paper | \ |
| 2024 | IEEE Transactions on Computational Social Systems | GANI | GANI: Global Attacks on Graph Neural Networks via Imperceptible Node Injections | MDP | Paper | Code |
| 2024 | Information Sciences | Song el al. | Two-level adversarial attacks for graph neural networks | MDP | Paper |
| Year | Venue | Model | Title | Algorithm | Paper | Code |
|---|---|---|---|---|---|---|
| 2017 | arXiv | Deeppath | Deeppath: A reinforcement learning method for knowledge graph reasoning | DQN | Paper | Code |
| 2017 | arXiv | KBGAN | KBGAN: Adversarial Learning for Knowledge Graph Embeddings | REINFORCE | Paper | Code |
| 2017 | ICLR | MINERVA | Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning | REINFORCE | Paper | Code |
| 2018 | IEEE ICDMW | MARLPaR | Path Reasoning over Knowledge Graph: A Multi-agent and Reinforcement Learning Based Method | MDP | Paper | \ |
| 2018 | KDD | DEERS | Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning | MDP | Paper | \ |
| 2018 | COLING | Chen et al. | Structured Dialogue Policy with Graph Neural Networks | REINFORCE | Paper | \ |
| 2018 | EMNLP | Lin et al. | Multi-Hop Knowledge Graph Reasoning with Reward Shaping | REINFORCE | Paper | \ |
| 2019 | arXiv | Graph2Seq | Reinforcement learning based graph-to-sequence model for natural question generation | MDP | Paper | Code |
| 2019 | arXiv | Ekar | Ekar: An Explainable Method for Knowledge Aware Recommendation | MDP | Paper | \ |
| 2019 | ACM SIGIR | PGPR | Reinforcement Knowledge Graph Reasoning for Explainable Recommendation | REINFORCE | Paper | Code |
| 2020 | ACM SIGIR | KGQR | Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning | DQN | Paper | \ |
| 2020 | arXiv | KG-A2C | Graph Constrained Reinforcement Learning for Natural Language Action Spaces | A2C | Paper | Code |
| 2020 | ACM SIGKDD | IMUP | Incremental Mobile User Profiling: Reinforcement Learning with Spatial Knowledge Graph for Modeling Event Streams | DQN | Paper | \ |
| 2020 | ICLR | RL-BIC | Causal Discovery with Reinforcement Learning | AC | Paper | Code |
| 2020 | arXiv | RL-HGNN | Reinforcement Learning Enhanced Heterogeneous Graph Neural Network | DQN | Paper | \ |
| 2020 | ISPA/BDCloud /SocialCom /SustainCom | DKDR | DKDR: An Approach of Knowledge Graph and Deep Reinforcement Learning for Disease Diagnosis | Q-Learning | Paper | \ |
| 2020 | KDD | NIRec | An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph | MDP | Paper | \ |
| 2020 | SIGIR | GCQN | Reinforcement Learning based Recommendation with Graph Convolutional Q-network | Q-Learning | Paper | \ |
| 2020 | Knowledge-Based Systems | GRL | GRL: Knowledge graph completion with GAN-based reinforcement learning | DDPG | Paper | \ |
| 2021 | ACM SIGIR | UNICORN | Unified conversational recommendation policy learning via graph-based reinforcement learning | DDQN | Paper | \ |
| 2021 | IEEE TNNLS | Sun et al. | Model-based transfer reinforcement learning based on graphical model representations | DDPG | Paper | \ |
| 2021 | arXiv | TITer | TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting | REINFORCE | Paper | Code |
| 2021 | Neurocomputing | MemoryPath | MemoryPath: A deep reinforcement learning framework for incorporating memory component into knowledge graph reasoning | MDP | Paper | \ |
| 2021 | IJCAI | CORL | Ordering-Based Causal Discovery with Reinforcement Learning | MDP | Paper | Code |
| 2021 | EMNLP-IJCNLP | AttnPath | Incorporating Graph Attention Mechanism into Knowledge Graph Reasoning Based on Deep Reinforcement Learning | MDP | Paper | \ |
| 2021 | Neural Networks | Dapath | Dapath: Distance-aware knowledge graph reasoning based on deep reinforcement learning | REINFORCE | Paper | Code |
| 2021 | IJCAI | RLH | Reasoning like human: Hierarchical reinforcement learning for knowledge graph reasoning | MDP | Paper | \ |
| 2020 | Knowledge-Based Systems | ADRL | ADRL: An attention-based deep reinforcement learning framework for knowledge graph reasoning | AC | Paper | \ |
| 2021 | IJCKG | PAAR | Multi-hop Knowledge Graph Reasoning Based on Hyperbolic Knowledge Graph Embedding and Reinforcement Learning | MDP | Paper | Code |
| 2021 | KSEM | Zheng et al. | Hierarchical Policy Network with Multi-agent for Knowledge Graph Reasoning Based on Reinforcement Learning | REINFORCE | Paper | \ |
| 2022 | Knowledge-Based Systems | RF | Dynamic knowledge graph reasoning based on deep reinforcement learning | AC | Paper | \ |
| 2022 | Applied Intelligence | RLPath | RLPath: a knowledge graph link prediction method using reinforcement learning based attentive relation path searching and representation learning | MDP | Paper | \ |
| 2022 | Soft Computing | GNNRC | A novel embedding learning framework for relation completion and recommendation based on graph neural network and multi-task learning | MDP | Paper | \ |
| 2022 | ACM/IMS Transactions on Data Science | TRGIR | A Text-based Deep Reinforcement Learning Framework Using Self-supervised Graph Representation for Interactive Recommendation | DDPG | Paper | \ |
| 2022 | arXiv | KGRGRL | KGRGRL: A User's Permission Reasoning Method Based on Knowledge Graph Reward Guidance Reinforcement Learning | MDP | Paper | \ |
| 2022 | AAAI | CURL | Learning to Walk with Dual Agents for Knowledge Graph Reasoning | MDP | Paper | Code |
| 2022 | arXiv | FreeKD | FreeKD: Free-direction Knowledge Distillation for Graph Neural Networks | MDP | Paper | \ |
| 2022 | ACM Transactions on Information Systems | Feng et al. | Reinforcement Routing on Proximity Graph for Efficient Recommendation | MDP | Paper | \ |
| 2022 | DASFAA | ExKGR | ExKGR: Explainable Multi-hop Reasoning for Evolving Knowledge Graph | MDP | Paper | \ |
| 2022 | DASFAA | Zhang et al. | A Joint Framework for Explainable Recommendation with Knowledge Reasoning and Graph Representation | A2C | Paper | \ |
| 2022 | Artificial Intelligence in Medicine | GTGAT | Gated Tree-based Graph Attention Network (GTGAT) for medical knowledge graph reasoning | MDP | Paepr | \ |
| 2022 | Education and Information Technologies | MEUR | Graph path fusion and reinforcement reasoning for recommendation in MOOCs | MDP | Paper | \ |
| 2022 | AICAT | Wu et al. | A construction technology of automatic reasoning system based on knowledge graph | MDP | Paper | \ |
| 2022 | Information Processing & Management | SparKGR | Iterative rule-guided reasoning over sparse knowledge graphs with deep reinforcement learning | DQN | Paper | \ |
| 2022 | arXiv | GRADER | Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning | MDP | Paper | \ |
| 2022 | arXiv | APPO | Performance Optimization for Semantic Communications: An Attention-based Reinforcement Learning Approach | MDP | Paper | \ |
| 2022 | arXiv | CERec | Reinforced Path Reasoning for Counterfactual Explainable Recommendation | MDP | Paper | Code |
| 2022 | ACM SIGIR | CGKR | Alleviating Spurious Correlations in Knowledge-aware Recommendations through Counterfactual Generator | MDP | Paper | Code |
| 2022 | ACM SIGIR | HICR | Conversational Recommendation via Hierarchical Information Modeling | DQN | Paper | \ |
| 2022 | ACM SIGIR | MARIS | Multi-Agent RL-based Information Selection Model for Sequential Recommendation | MDP | Paper | \ |
| 2022 | ICME | ROGC | ROGC: Role-Oriented Graph Convolution Based Multi-Agent Reinforcement Learning | MARL | Paper | \ |
| 2022 | AAAI | HiTKG | HiTKG: Towards Goal-Oriented Conversations via Multi-Hierarchy Learning | MDP | Paper | \ |
| 2022 | Applied Soft Computing | SSRL | Self-Supervised Reinforcement Learning with dual-reward for knowledge-aware recommendation | Actor-Critic | Paper | \ |
| 2022 | Knowledge-Based Systems | KAiPP | KAiPP: An interaction recommendation approach for knowledge aided intelligent process planning with reinforcement learning | MDP | Paper | \ |
| 2022 | CIKM | KRAF | A Flexible Advertising Framework using Knowledge Graph-Enriched Multi-Agent Reinforcement Learning | MARL | Paper | \ |
| 2022 | CIKM | GPR | Two-Level Graph Path Reasoning for Conversational Recommendation with User Realistic Preference | DQN | Paper | \ |
| 2022 | SSRN | VRNet | Knowledge Graph Relation Reasoning with Variational Reinforcement Network | MDP | Paper | \ |
| 2022 | KBS | Zhu et al. | Step by step: A hierarchical framework for multi-hop knowledge graph reasoning with reinforcement learning | MDP | Paper | Code |
| 2022 | Applied Intelligence | Xia et al. | Reason more like human: Incorporating meta information into hierarchical reinforcement learning for knowledge graph reasoning | MDP | Paper | \ |
| 2023 | SDM | GARL | Causal Discovery by Graph Attention Reinforcement Learning | MDP | Paper | \ |
| 2023 | Education and Information Technologies | MEUR | Graph path fusion and reinforcement reasoning for recommendation in MOOCs | Actor-Critic | Paper | \ |
| 2023 | IEEE TKDE | TMER-RL | Reinforcement Learning based Path Exploration for Sequential Explainable Recommendation | MDP | Paper | \ |
| 2023 | CLeaR | MCD | A Meta-Reinforcement Learning Algorithm for Causal Discovery | Actor-Critic | Paper | Code |
| 2023 | Applied Intelligence | RED | Reinforcement learning-based denoising network for sequential recommendation | MDP | Paper | \ |
| 2023 | Conference of the European Chapter of the Association for Computational Linguistics | Jiang et al. | Path Spuriousness-aware Reinforcement Learning for Multi-Hop Knowledge Graph Reasoning | REINFORCE | Paper | Code |
| 2023 | SIGIR | DREAM | DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning | MDP | Paper | \ |
| 2023 | Information Sciences | ARN | Incorporating anticipation embedding into reinforcement learning framework for multi-hop knowledge graph question answering | REINFORCE | Paper | Code |
| 2023 | Knowledge-Based Systems | RLAT | RLAT: Multi-hop temporal knowledge graph reasoning based on Reinforcement Learning and Attention Mechanism | MDP | Paper | \ |
| 2023 | Information Processing & Management | DCRN | Reinforcement learning with dynamic completion for answering multi-hop questions over incomplete knowledge graph | MDP | Paper | Code |
| 2023 | Machine Learning and Knowledge Discovery in Databases | FITCARL | Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs Using Confidence-Augmented Reinforcement Learning | MDP | Paper | Code |
| 2023 | Expert Systems with Applications | TRISONIC | Complex relationship graph abstraction for autonomous air combat collaboration: A learning and expert knowledge hybrid approach | MADRL | Paper | \ |
| 2024 | arXiv | KGM | Enhancing Multi-Hop Knowledge Graph Reasoning through Reward Shaping Techniques | REINFORCE | Paper | \ |
| 2024 | Information Sciences | Ae2KGR | Attention-based exploitation and exploration strategy for multi-hop knowledge graph reasoning | MDP | Paper | \ |
| Year | Venue | Model | Title | Algorithm | Paper | Code |
|---|---|---|---|---|---|---|
| 2019 | NeurIPS | GMETAEXP | Learning Transferable Graph Exploration | MDP | Paper | \ |
| 2019 | arXiv | Ekar | Ekar: An Explainable Method for Knowledge Aware Recommendation | MDP | Paper | \ |
| 2019 | ACM SIGIR | PGPR | Reinforcement Knowledge Graph Reasoning for Explainable Recommendation | REINFORCE | Paper | Code |
| 2020 | KDD | XGNN | XGNN: Towards Model-Level Explanations of Graph Neural Networks | MDP | Paper | \ |
| 2021 | ICML | SubgraphX | On Explainability of Graph Neural Networks via Subgraph Explorations | MCTS | Paper | Code |
| 2021 | arXiv | SparRL | SparRL: Graph Sparsification via Deep Reinforcement Learning | MDP | Paper | Code |
| 2021 | ACM TOIS | RioGNN | Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks | MDP | Paper | Code |
| 2022 | ICLR | G2RL | Graph-Enhanced Exploration for Goal-oriented Reinforcement Learning | Q-Learning | Paper | \ |
| 2022 | IEEE TNNLS | LEGIT | Explaining Deep Graph Networks via Input Perturbation | MDP | Paper | Code |
| 2022 | ADC | Mishra et al. | Predicting Taxi Hotspots in Dynamic Conditions Using Graph Neural Network | MDP | Paper | \ |
| 2022 | CIKM | Saha et al. | A Model-Centric Explainer for Graph Neural Network based Node Classification | REINFORCE | Paper | Code |
| Year | Venue | Model | Title | Algorithm | Paper | Code |
|---|---|---|---|---|---|---|
| 2018 | IEEE Big Data | Obara et al. | Deep Reinforcement Learning Approach for Train Rescheduling Utilizing Graph Theory | DQN | Paper | \ |
| 2018 | PMLR | Zhang et al. | Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents. | Actor-Critic | Paper | \ |
| 2018 | IEEE ITSC | NFQI | Traffic Signal Control Based on Reinforcement Learning with Graph Convolutional Neural Nets | NFQI | Paper | \ |
| 2019 | SOSR | Rusek et al. | Unveiling the potential of Graph Neural Networks for network modeling and optimization in SDN | MDP | Paper | \ |
| 2019 | arXiv | DRL+GNN | Deep Reinforcement Learning meets Graph Neural Networks: exploring a routing optimization use case | DQN | Paper | Code |
| 2019 | SIGCOMM | RouteNet | Challenging the generalization capabilities of graph neural networks for network modeling | MDP | Paper | \ |
| 2020 | IJCAI | eGCN | Dynamic Electronic Toll Collection via Multi-Agent Deep Reinforcement Learning with Edge-Based Graph Convolutional Networks | MDP | Paper | \ |
| 2020 | IEEE TMC | STMARL | STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control | DQN | Paper | \ |
| 2020 | IEEE Access | NAKASHIMA et al. | Deep Reinforcement Learning-Based Channel Allocation for Wireless LANs With Graph Convolutional Networks | DDQN | Paper | \ |
| 2020 | Artificial Intelligence in China | DR-DCG | Coordinated Learning for Lane Changing Based on Coordination Graph and Reinforcement Learning | MDP | Paper | \ |
| 2021 | IEEE ICCCS | GraphLight | GraphLight: Graph-based Reinforcement Learning for Traffic Signal Control | REINFORCE | Paper | \ |
| 2021 | IEEE T-ITS | IG-RL | IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control | MDP | Paper | Code |
| 2021 | Computer‐Aided Civil and Infrastructure Engineering | GCQ | Graph neural network and reinforcement learning for multi-agent cooperative control of connected autonomous vehicles | DQN | Paper | \ |
| 2021 | IEEE T-ITS | SAGE-Garph | Deep Reinforcement Learning With Graph Representation for Vehicle Repositioning | DDQN | Paper | \ |
| 2021 | Information Sciences | Dynamic graph | Dynamic graph convolutional network for long-term traffic flow prediction with reinforcement learning | PPO | Paper | \ |
| 2022 | Digital Signal Processing | DQN-GCN-GAT | A new ensemble deep graph reinforcement learning network for spatio-temporal traffic volume forecasting in a freeway network | DQN | Paper | \ |
| 2022 | IEEE TMC | RedPacketBike | RedPacketBike: A Graph-Based Demand Modeling and Crowd-Driven Station Rebalancing Framework for Bike Sharing Systems | MDP | Paper | \ |
| 2022 | International Journal of Electrical Power & Energy Systems | GRL | Real-time fast charging station recommendation for electric vehicles in coupled power-transportation networks: A graph reinforcement learning method | DQN | Paper | \ |
| 2022 | Digital Signal Processing | DQN-GCN-GAT | A new ensemble deep graph reinforcement learning network for spatio-temporal traffic volume forecasting in a freeway network | DQN | Paper | \ |
| 2022 | arXiv | MuJAM | Model-based graph reinforcement learning for inductive traffic signal control | MDP | Paper | \ |
| 2022 | Applied Intelligence | GCQN-TSC | Graph cooperation deep reinforcement learning for ecological urban traffic signal control | MDP | Paper | \ |
| 2022 | arXiv | GRL | Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments | DQN | Paper | Code |
| 2022 | Knowledge-Based Systems | MetaSTGAT | Meta-learning based spatial-temporal graph attention network for traffic signal control | DQN | Paper | \ |
| 2022 | Applied Intelligence | VARL | VARL: a variational autoencoder-based reinforcement learning Framework for vehicle routing problems | MDP | Paper | \ |
| 2022 | Information Fusion | IHA-MDGI | An inductive heterogeneous graph attention-based multi-agent deep graph infomax algorithm for adaptive traffic signal control | multi-agent ATSC | Paper | \ |
| 2022 | Transportation Research Part C: Emerging Technologies | RDGCNI | A novel reinforced dynamic graph convolutional network model with data imputation for network-wide traffic flow prediction | DDPG | Paper | \ |
| 2022 | IJECE | ERL-MA | Evolutionary reinforcement learning multi-agents system for intelligent traffic light control: new approach and case of study | Q-Learning | Paper | \ |
| 2022 | IEEE Internet of Things Journal | GCN-based DRL | Joint Routing and Scheduling Optimization in Time-Sensitive Networks Using Graph Convolutional Network-based Deep Reinforcement Learning | DQN | Paper | \ |
| 2022 | Artificial Intelligence and Computing on Industrial Applications | MB-GCN | A Deep Coordination Graph Convolution Reinforcement Learning for Multi-Intelligent Vehicle Driving Policy | MDP | Paper | \ |
| 2022 | IET Communications | GRL | A generic intelligent routing method using deep reinforcement learning with graph neural networks | PPO | Paper | \ |
| 2022 | CIKM | Lou et al | Meta-Reinforcement Learning for Multiple Traffic Signals Control | MDP | Paper | \ |
| 2022 | IEEE ICIEA | GCN-DQN/GCN-DDQN | Multi-Vehicles Decision-Making in Interactive Highway Exit: A Graph Reinforcement Learning Approach | DQN/DDQN | Paper | \ |
| 2022 | IEEE ITSC | Liu et al. | Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Interactive Traffic Scenarios | MDP | Paper | Code |
| 2022 | arXiv | MuJAM | Model-based graph reinforcement learning for inductive traffic signal control | MDP | Paper | \ |
| 2023 | IET Gener. Transm. Distrib. | GraphSAGE-D3QN | An emergency control strategy for undervoltage load shedding of power system: A graph deep reinforcement learning method | D3QN | Paper | \ |
| 2023 | Information Sciences | HG-M2I | Hierarchical graph multi-agent reinforcement learning for traffic signal control | MARL | Paper | \ |
| 2024 | Transportation Research Part C: Emerging Technologies | MGMQ | A large-scale traffic signal control algorithm based on multi-layer graph deep reinforcement learning | Q-Learning | Paper | \ |
| Year | Venue | Model | Title | Algorithm | Paper | Code |
|---|---|---|---|---|---|---|
| 2020 | Nature Machine Intelligence | FINDER | Finding key players in complex networks through deep reinforcement learning | Q-Learning | Paper | Code |
| 2021 | ICML | RLGN | Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks | PPO | Paper | \ |
| 2021 | IEEE TNNLS | FOREST | Full-Scale Information Diffusion Prediction With Reinforced Recurrent Networks | REINFORCE | Paper | Code |
| 2021 | arXiv | HITTER | Hypernetwork Dismantling via Deep Reinforcement Learning | DQN | Paper | \ |
| 2022 | IEEE TETCI | EDRL-IM | Influence Maximization in Complex Networks by Using Evolutionary Deep Reinforcement Learning | DQN | Paper | \ |
| 2022 | ACM Transactions on Knowledge Discovery from Data | IDRLECA | Contact Tracing and Epidemic Intervention via Deep Reinforcement Learning | PPO | Paper | \ |
| 2022 | KDD | Vehicle | Precise Mobility Intervention for Epidemic Control Using Unobservable Information via Deep Reinforcement Learning | HRL | Paper | \ |
| Year | Venue | Model | Title | Algorithm | Paper | Code |
|---|---|---|---|---|---|---|
| 2017 | NIPS | S2V-DQN | Learning Combinatorial Optimization Algorithms over Graphs | Q-Learning | Paper | Code |
| 2018 | AAAI | ASNets | Action Schema Networks: Generalised Policies with Deep Learning | MDP | Paper | Code |
| 2019 | arXiv | GPN | Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning | REINFORCE | Paper | Code |
| 2020 | Nature Machine Intelligence | FINDER | Finding key players in complex networks through deep reinforcement learning | Q-Learning | Paper | Code |
| 2021 | IEEE Communications Letters | DeepOpt | Combining Deep Reinforcement Learning With Graph Neural Networks for Optimal VNF Placement | REINFORCE | Paper | \ |
| 2020 | IEEE Access | SILVA et al. | Temporal Graph Traversals Using Reinforcement Learning With Proximal Policy Optimization | PPO | Paper | \ |
| 2022 | IEEE TETCI | EDRL-IM | Influence Maximization in Complex Networks by Using Evolutionary Deep Reinforcement Learning | DQN | Paper | \ |
| 2022 | arXiv | GTA-RL | Solving Dynamic Graph Problems with Multi-Attention Deep Reinforcement Learning | REINFORCE | Paper | Code |
| 2022 | IEEE TII | Song et al. | Flexible Job Shop Scheduling via Graph Neural Network and Deep Reinforcement Learning | PPO | Paper | \ |
| 2022 | Engineering Applications of Artificial Intelligence | GCE-MAD | A graph convolutional encoder and multi-head attention decoder network for TSP via reinforcement learning | REINFORCE | Paper | \ |
| 2022 | IEEE TII | DGERD | A Deep Reinforcement Learning Framework Based on an Attention Mechanism and Disjunctive Graph Embedding for the Job Shop Scheduling Problem | DQN | Paper | \ |
| 2022 | arXiv | ECORD | Learning to Solve Combinatorial Graph Partitioning Problems via Efficient Exploration | DQN | Paper | Code |
| 2022 | Information Sciences | G3DQN | A graph neural networks-based deep Q-learning approach for job shop scheduling problems in traffic management | DQN | Paper | \ |
| 2022 | KDD | DGMP | Enhancing Machine Learning Approaches for Graph Optimization Problems with Diversifying Graph Augmentation | MDP | Paper | \ |
| 2022 | Neurocomputing | E-GAT | Solve routing problems with a residual edge-graph attention neural network | PPO | Paper | Code |
| 2022 | arXiv | N-BLS | Subgraph Matching via Query-Conditioned Subgraph Matching Neural Networks and Bi-Level Tree Search | MCTS | Paper | \ |
| 2022 | techrxiv | TOFA | You Only Train Once: A highly generalizable reinforcement learning method for dynamic job shop scheduling problem | MDP | Paper | Code |
| 2022 | arXiv | LKH | Solving the Traveling Salesperson Problem with Precedence Constraints by Deep Reinforcement Learning | MDP | Paper | Code |
| 2022 | IEEE TII | DRL | Flexible job-shop scheduling via graph neural network and deep reinforcement learning | PPO | Paper | Code |
| 2022 | Journal of Intelligent Manufacturing | GMAS | Multi-agent reinforcement learning based on graph convolutional network for flexible job shop scheduling | MARL | Paper | \ |
| 2023 | Knowledge-Based Systems | DeepMAG | DeepMAG: Deep reinforcement learning with multi-agent graphs for flexible job shop scheduling | MARL | Paper | \ |
| 2023 | Information Sciences | BDRL | Solving combinatorial optimization problems over graphs with BERT-Based Deep Reinforcement Learning | REINFORCE | Paper | \ |
| 2023 | Applied Soft Computing | DJSP | Evolution strategies-based optimized graph reinforcement learning for solving dynamic job shop scheduling problem | MDP | Paper | \ |
| 2023 | Journal of Manufacturing Systems | DRLG | A novel priority dispatch rule generation method based on graph neural network and reinforcement learning for distributed job-shop scheduling | Actor-Critic | Paper | \ |
| 2024 | IEEE Transactions on Computational Social Systems | ToupleGDD | ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning | DQN | Paper | Code |
| Year | Venue | Model | Title | Algorithm | Paper | Code |
|---|---|---|---|---|---|---|
| 2018 | NeurIPS | GCPN | Graph convolutional policy network for goal-directed molecular graph generation | MDP | Paper | Code |
| 2018 | arXiv | MolGAN | MolGAN: An implicit generative model for small molecular graphs | MDP | Paper | \ |
| 2019 | CIKM | CompNet | Order-free Medicine Combination Prediction with Graph Convolutional Reinforcement Learning | DQN | Paper | Code |
| 2019 | KDD | GTPN | Graph Transformation Policy Network for Chemical Reaction Prediction | A2C | Paper | \ |
| 2020 | IEEE Access | Wang et al. | Risk-Aware Identification of Highly Suspected COVID-19 Cases in Social IoT: A Joint Graph Theory and Reinforcement Learning Approach | Q-Learning | Paper | \ |
| 2020 | ISPA/BDCloud /SocialCom /SustainCom | DKDR | DKDR: An Approach of Knowledge Graph and Deep Reinforcement Learning for Disease Diagnosis | Q-Learning | Paper | \ |
| 2020 | Journal of cheminformatics | DeepGraphMolGen | DeepGraphMolGen, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach | PPO | Paper | Code |
| 2022 | arXiv | BN-GNN | Deep Reinforcement Learning Guided Graph Neural Networks for Brain Network Analysis | DDQN | Paper | \ |
| 2023 | Aiche Journal | Stops et al. | Flowsheet generation through hierarchical reinforcement learning and graph neural networks | Actor-Critic | Paper | \ |
| Year | Venue | Model | Title | Algorithm | Paper | Code |
|---|---|---|---|---|---|---|
| 2017 | IEEE TNNLS | FRDNN | Deep direct reinforcement learning for financial signal representation and trading | DRL | Paper | \ |
| 2018 | ICLR | NerveNet | NerveNet: Learning Structured Policy with Graph Neural Networks | PPO | Paper | \ |
| 2020 | ACM/IEEE DAC | GCN-RL | GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning | AC | Paper | \ |
| 2021 | Expert Systems with Applications | DeepPocket | Deep graph convolutional reinforcement learning for financial portfolio management-deeppocket | AC | Paper | \ |
| 2021 | arXiv | Gnn-rl compression | Gnn-rl compression: Topologyaware network pruning using multi-stage graph embedding and reinforcement learning | DDPG | Paper | \ |
| 2021 | ICCV | AGMC | Auto graph encoder-decoder for neural network pruning | DQN | Paper | \ |
| 2022 | Applied Intelligence | GraphPruning | Graph pruning for model compression | DDPG | Paper | \ |
| 2022 | ICLR | AGILE | Know Your Action Set: Learning Action Relations for Reinforcement Learning | PPO\DQN\CDQN | Paper | Code |
| 2022 | ICLR | MAPSRL-2 | Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory | Q-Learning | Paper | \ |
| 2022 | ICLR | SWAT | Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning | AC | Paper | \ |
| 2022 | IEEE TPAMI | DRL-DBSCAN | Reinforced, Incremental and Cross-lingual Event Detection From Social Messages | MarGNN | Paper | Code |
| 2022 | ACM Transactions on Asian and Low-Resource Language Information Processing | GA-SCS | GA-SCS: Graph-Augmented Source Code Summarization | MDP | Paper | \ |
| 2022 | IP CCC | RCGNN | Reinforced Contrastive Graph Neural Networks (RCGNN) for Anomaly Detection | Recursive Scalable Reinforcement Learning (RSRL) | Paper | \ |
| 2022 | IEEE Transactions on Computational Social Systems | MADDPG | Misinformation Propagation in Online Social Networks: Game Theoretic and Reinforcement Learning Approaches | MARL | Paper | \ |
| 2024 | IEEE Transactions on Intelligent Vehicles | GRL | Graph Reinforcement Learning for Multi-Aircraft Conflict Resolution | MDP | Paper | \ |
| 2024 | arXiv | GCBR | Class-Balanced and Reinforced Active Learning on Graphs | A2C | Paper | \ |
| 2024 | Expert Systems with Applications | DWRL | DeepWalk with Reinforcement Learning (DWRL) for node embedding | MDP | Paper | \ |
| 2024 | Expert Systems with Applications | SCN_GNN | SCN_GNN: A GNN-based fraud detection algorithm combining strong node and graph topology information | MDP | Paper | \ |