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Research on incentive mechanism design in mobile crowdsensing and mobile edge computing by deep reinforcement learning approaches.

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Overview

Research on DRL + Networking systems, including mobile crowdsensing system, edge computing, federated learning.

References

[1] Y. Zhan, S. Guo, P. Li and J. Zhang, "A Deep Reinforcement Learning Based Offloading Game in Edge Computing," in IEEE Transactions on Computers, vol. 69, no. 6, pp. 883-893, 1 June 2020, doi: 10.1109/TC.2020.2969148.

[2] Y. Zhan, J. Zhang, "An Incentive Mechanism Design for Efficient Edge Learning by Deep Reinforcement Learning Approach," in INFOCOM 2020.

[3] Y. Zhan, P. Li and S. Guo, "Experience-Driven Computational Resource Allocation of Federated Learning by Deep Reinforcement Learning," 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), New Orleans, LA, USA, 2020, pp. 234-243, doi: 10.1109/IPDPS47924.2020.00033.

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Research on incentive mechanism design in mobile crowdsensing and mobile edge computing by deep reinforcement learning approaches.

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