BIT-MCS

DRL-EC3

[JSAC 2018] Energy-Efficient UAV Control for Effective and Fair Communication Coverage: A Deep Reinforcement Learning Approach

GCRL-min-AoI

[INFOCOM 2022] AoI-minimal UAV Crowdsensing by Model-based Graph Convolutional Reinforcement Learning

DRL-eFresh

[TMC 2023] Delay-Sensitive Energy-Efficient UAV Crowdsensing by Deep Reinforcement Learning

Cadre

[AAAI 2022] CADRE: A Cascade Deep Reinforcement Learning Framework for Vision-based Autonomous Urban Driving

e-Divert

[TMC 2021] Distributed and Energy-Efficient Mobile Crowdsensing with Charging Stations by Deep Reinforcement Learning

human_drone_SC

[ICDE 2022] Human-Drone Collaborative Spatial Crowdsourcing by Memory-Augmented Distributed Multi-Agent Deep Reinforcement Learning

DRL-SIM

[TITS 2021] Social-aware incentive mechanism for vehicular crowdsensing by deep reinforcement learning

DRL-CEWS

[ICDE 2020] Curiosity-Driven Energy-Efficient Worker Scheduling in Vehicular Crowdsourcing: A Deep Reinforcement Learning Approach

DRL-freshMCS

[INFOCOM 2021] Mobile Crowdsensing for Data Freshness: A Deep Reinforcement Learning Approach

DRL-MTVCS

[INFOCOM 2020] Multi-Task-Oriented Vehicular Crowdsensing: A Deep Learning Approach

jPPO-ConvNTM

[INFOCOM 2020] Energy-Efficient UAV Crowdsensing with Multiple Charging Stations by Deep Learning

DRL-DisasterVC

[KDD 2021] Energy-Efficient 3D Vehicular Crowdsourcing for Disaster Response by Distributed Deep Reinforcement Learning

hi-MADRL

[ICDE 2023] Exploring both Individuality and Cooperation for Air-Ground Spatial Crowdsourcing by Multi-Agent Deep Reinforcement Learning

Edics

[JSAC 2019] Energy-Efficient Distributed Mobile Crowd Sensing: A Deep Learning Approach

DRL-UCS-AoI-Threshold

[ToN 2024] Ensuring Threshold AoI for UAV-assisted Mobile Crowdsensing by Multi-Agent Deep Reinforcement Learning with Transformer

AttConvLSTM

[ICDE 2021] Modeling Citywide Crowd Flows using Attentive Convolutional LSTM

Time-Aware-Location-Prediction

[TKDE 2022] Time-Aware Location Prediction by Convolutional Area-of-Interest Modeling and Memory-Augmented Attentive LSTM

MADRL-PosVCS

SIMS

[TNSE 2021] Modeling User Interests With Online Social Network Influence by Memory Augmented Sequence Learning