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陈春林

领域:高端装备制造产业 学校:南京大学职称:教授

机器学习与随机优化,及其在复杂系统管理与控制中的应用,包括:强化学习、智能无人系统、量子控制。


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教育背景

工作经历

项目课题经历

先后主持国家自然科学基金项目及企业项目等10余项,作为主要完成者参与其他国家重点专项、国家自然科学基金及企业横向课题10余项。

论文、成果、著作等

[24]Incremental Reinforcement Learning in Continuous Spaces via Policy Relaxation and Importance Weighting. IEEE Transactions on Neural Networks and Learning Systems, preprint online, Doi: 10.1109/TNNLS.2019.2927320.


[23]Learning-based Quantum Robust Control: Algorithm, Applications and Experiments. IEEE Transactions on Cybernetics, preprint online, Doi: 10.1109/TCYB.2019.2921424.


[22]Reinforcement Learning Based Optimal Sensor Placement for Spatiotemporal Modeling. IEEE Transactions on Cybernetics, preprint online, Doi: 10.1109/TCYB.2019.2901897, 2019.


[21]Incremental Reinforcement Learning with Prioritized Sweeping for Dynamic Environments. IEEE/ASME Transactions on Mechatronics, 24(2): 621-632, 2019.


[20]Self-paced prioritized curriculum learning with coverage penalty in deep reinforcement learning. IEEE Transactions on Neural Networks and Learning Systems, 29(6): 2216-2226, 2018.


[19]Robust learning control design for quantum unitary transformations. IEEE Transactions on Cybernetics, 47(12): 4405-4417, 2017.


[18]Quantum Learning Control Using Differential Evolution with Equally-mixed Strategies, Control Theory and Technology, 15(3): 226-241, 2017.


[17]Multi-agent Reinforcement Learning with Sparse Interactions by Negotiation and Knowledge Transfer. IEEE Transactions on Cybernetics, 47(5): 1238-1250, 2017.


[16]Quantum Ensemble Classification: A Sampling-based Learning Control Approach. IEEE Transactions on Neural Networks and Learning Systems, 28(6): 1345-1359, 2017.

[15]Learning robust pulses for generating universal quantum gates, Scientific Reports, 6: 36090, 2016.

[14]Robust manipulation of superconducting qubits in the presence of fluctuations, Scientific Reports, 5: 7873, 2015.


[13]Sampling-based learning control for quantum systems with uncertainties, IEEE Transactions on Control Systems Technology, 23(6): 2155-2166, 2015.


[12]Fidelity-based Probabilistic Q-learning for Control of Quantum Systems. IEEE Transactions on Neural Networks and Learning Systems, 25(5): 920-933, 2014.


[11]Sampling-based Learning Control of Inhomogeneous Quantum Ensembles. Physical Review A, 89: 023402, 2014.


[10]Sampling-based Learning Control of Quantum Systems via Path Planning. IET Control Theory and Applications, 8(15): 1513-1522, 2014.


[9]Further results on sampled-data design for robust control of a single qubit, International Journal of Control, 87(10): 2056-2064, 2014.


[8]Control Design of Uncertain Quantum Systems with Fuzzy Estimators. IEEE Transactions on Fuzzy Systems, 20(5): 820-831, 2012.


[7]Robust Quantum-Inspired Reinforcement Learning for Robot Navigation.IEEE-ASME Transactions on Mechatronics, 17(1): 86-97, 2012.


[6]Probabilistic Fuzzy System for Uncertain Localization and Map-Building of Mobile Robots. IEEE Transactions on Instrumentation and Measurement, 61(6): 1546-1560, 2012.


[5]Hybrid MDP Based Integrated Hierarchical Q-learning. Science China Information Sciences, 54(11): 2279-2294, 2011.


[4]Incoherent Control of Quantum Systems with Wavefunction Controllable Subspaces via Quantum Reinforcement Learning. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 38(4): 957-962, 2008.


[3]Quantum Reinforcement Learning. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 38(5): 1207-1220, 2008.


[2]Hybrid Control for Robot Navigation - A Hierarchical Q-Learning Algorithm. IEEE Robotics & Automation Magazine, 15(2): 37-47, 2008.


[1]Quantum Computation for Action Selection Using Reinforcement Learning. International Journal of Quantum Information, 4(6): 1071-1083, 2006.


《自动化导论》(第二版,副主编),科学出版社,北京,2014年8月.

专利、著作版权等

申请国家发明专利12项,其中已获授权3项。

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