教育背景：

2008-2012 阜陽師范大學(xué),，計(jì)算機(jī)科學(xué)與技術(shù)學(xué)士

2013-2016 昆明理工大學(xué)，軟件工程碩士

2017-2022 上海大學(xué),，    計(jì)算機(jī)應(yīng)用技術(shù)博士

職業(yè)經(jīng)歷：

2012-2013 南京睿辰欣創(chuàng)網(wǎng)絡(luò)科技有限公司,，研發(fā)

2016-2017 上海明匠智能系統(tǒng)有限公司，研發(fā)

研究方向：

強(qiáng)化學(xué)習(xí),，多智能體強(qiáng)化學(xué)習(xí),，智能決策

參與項(xiàng)目：

1）國(guó)家自然科學(xué)基金重大項(xiàng)目；項(xiàng)目名稱：復(fù)雜海況典型無人艇集群應(yīng)用驗(yàn)證平臺(tái)研究,；項(xiàng)目編號(hào)：61991415,。 

2）上海市2020年度科技創(chuàng)新行為計(jì)劃；項(xiàng)目名稱：融合知識(shí)的無人艇自主行

為決策方法,；項(xiàng)目編號(hào)：20YF1413800,。

科研成果：

[1] Wang W, Luo X, Li Y, et al. Unmanned surface vessel obstacle avoidance with prior knowledgebased reward shaping[J]. Concurrency and Computation: Practice and Experience, 2021. (SCI 期刊)

[2] Wang W, Zhang H, LiY, et al. USVsSim: Ageneral simulation platformfor unmanned surface vessels autonomous learning[J]. Concurrency and Computation: Practice and Experience, 2022. (SCI 期刊)

[3] Wang W, Li Y, Luo X, et al. Ocean image data augmentation in the USV virtual training scene[J]. Big Earth Data, 2020, 4(4): 451-463. (EI 期刊)

[4] Wang W, Xiangfeng Luo. Autonomous docking of the USV using Deep Reinforcement learning combine with observation enhanced, 2021 IEEE international Conference on Advances in Electrical Engineering and Computer Applications(AAEECA). (EI 會(huì)議)

[5] Li Y, Wang X, Wang W, et al. Learning adversarial policy in multiple scenes environment via multi-agent reinforcement learning[J]. Connection Science, 2021, 33(3): 407-426.(SCI期刊)

[6] Wang J, Wang X, Luo X, Wang W et al. SEM: Adaptive Staged Experience Access Mechanism for Reinforcement Learning[C]//2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2020: 1088-1095. (EI 會(huì)議)

[7] Zhang Z, Luo X, Liu T, Wang W et al. Proximal policy optimization with mixed distributed training[C]//2019 IEEE 31st international conference on tools with artificial intelligence (ICTAI). IEEE, 2019: 1452-1456. (EI 會(huì)議)