Deep Reinforcement Learning for Task Allocation in Energy Harvesting Mobile Crowdsensing
Author:
Affiliation:
1. Technical University of Darmstadt,Communications Engineering Lab,Germany
Funder
German Research Foundation (DFG)
Collaborative Research Center (CRC)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10000063/10000593/10001204.pdf?arnumber=10001204
Reference16 articles.
1. Task Allocation for Mobile Crowdsensing with Deep Reinforcement Learning
2. Efficient Task Allocation for Mobile Crowd Sensing Based on Evolutionary Computing
3. A Two-Layer Reinforcement Learning Solution for Energy Harvesting Data Dissemination Scenarios
4. Energy-Aware Participant Selection for Smartphone-Enabled Mobile Crowd Sensing
5. CrowdRecruiter
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2. Improved Deep Deterministic Policy Gradient Algorithm based on PER for Partial Task Offloading;2024 IEEE Wireless Communications and Networking Conference (WCNC);2024-04-21
3. Federated Deep Reinforcement Learning for Task Participation in Mobile Crowdsensing;GLOBECOM 2023 - 2023 IEEE Global Communications Conference;2023-12-04
4. A task allocation and pricing mechanism based on Stackelberg game for edge-assisted crowdsensing;Wireless Networks;2023-11-15
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