BIT-MCS / DRL-MTVCS
[INFOCOM 2020] Multi-Task-Oriented Vehicular Crowdsensing: A Deep Learning Approach
☆14Updated 2 years ago
Alternatives and similar repositories for DRL-MTVCS:
Users that are interested in DRL-MTVCS are comparing it to the libraries listed below
- [TITS 2021] Social-aware incentive mechanism for vehicular crowdsensing by deep reinforcement learning☆16Updated 2 years ago
- [INFOCOM 2021] Mobile Crowdsensing for Data Freshness: A Deep Reinforcement Learning Approach☆14Updated 2 years ago
- [TMC 2021] Distributed and Energy-Efficient Mobile Crowdsensing with Charging Stations by Deep Reinforcement Learning☆26Updated 2 years ago
- [INFOCOM 2020] Energy-Efficient UAV Crowdsensing with Multiple Charging Stations by Deep Learning☆16Updated 2 years ago
- [JSAC 2019] Energy-Efficient Distributed Mobile Crowd Sensing: A Deep Learning Approach☆13Updated 2 years ago
- [ICDE 2022] Human-Drone Collaborative Spatial Crowdsourcing by Memory-Augmented Distributed Multi-Agent Deep Reinforcement Learning☆24Updated 2 years ago
- [TMC 2023] Delay-Sensitive Energy-Efficient UAV Crowdsensing by Deep Reinforcement Learning☆44Updated 2 years ago
- [INFOCOM 2022] AoI-minimal UAV Crowdsensing by Model-based Graph Convolutional Reinforcement Learning☆49Updated last year
- [ToN 2024] Ensuring Threshold AoI for UAV-assisted Mobile Crowdsensing by Multi-Agent Deep Reinforcement Learning with Transformer☆23Updated last year
- [ICDE 2020] Curiosity-Driven Energy-Efficient Worker Scheduling in Vehicular Crowdsourcing: A Deep Reinforcement Learning Approach☆16Updated 2 years ago
- The visualization of a multi-agent reinforcement learning (MARL)-based strategy with efficient exploration strategy.☆17Updated 2 years ago
- Code for paper Social-Aware Incentive Mechanism for Vehicular Crowdsensing by Deep Reinforcement Learning☆21Updated 2 years ago
- This is the code for paper: Scalable Federated Multi-agent Architecture forNetworked Communication Scenarios☆18Updated 3 years ago
- User allocation in Mobile Edge Computing Environment using Reinforcement Learning☆27Updated 2 years ago
- Codes for the paper titled Online Joint Task Offloading and Resource Management in Heterogeneous Mobile Edge Environments.☆13Updated 2 years ago
- ☆12Updated 3 years ago
- Simulation code for the paper "Resource Allocation in V2X Networks: From Classical Optimization to Machine Learning-based Solutions"☆14Updated 9 months ago
- Code for IEEE GLOBECOM 2023 paper "Caching for Edge Inference at Scale: A Mean Field Multi-Agent Reinforcement Learning Approach".☆10Updated 8 months ago
- qiongwu86 / Resource-allocation-for-twin-maintenance-and-computing-tasks-in-digital-twin-mobile-edge-network☆20Updated 7 months ago
- ☆32Updated 2 years ago
- code☆12Updated last year
- [KDD 2021] Energy-Efficient 3D Vehicular Crowdsourcing for Disaster Response by Distributed Deep Reinforcement Learning☆14Updated 2 years ago
- ☆19Updated 10 months ago
- ☆25Updated 3 years ago
- Deep Reinforcement Learning Environments for User-Centric Mobile Edge Computing☆23Updated 10 months ago
- Implementation of the article 'A Strategic Game for Task Offloading among Capacitated UAV-mounted Cloudlets'☆12Updated 2 years ago
- Decision making using Reinforcement Learning☆21Updated 5 years ago
- The purpose of this project is to implement machine learning methods to study resource allocation problems, that is how to share limited …☆15Updated 2 years ago
- ☆31Updated 2 years ago
- 车联网环境☆17Updated last year