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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.1//EN"
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<title>Zhi Wang</title>
</head>
<body>
<table summary="Table for page layout." id="tlayout">
<tr valign="top">
<td id="layout-menu">
<div class="menu-category">Menu</div>
<div class="menu-item"><a href="index.html">Home</a></div>
<div class="menu-item"><a href="publication.html" class="current">Publications</a></div>
<div class="menu-item"><a href="teaching.html">Teaching</a></div>
</td>
<td id="layout-content">
<div id="toptitle">
<h1>Selected Papers </h1>
</div>
<h3>Preprints</h3>
<ul>
<li><p>Jinmei Liu, Wenbin Li, Xiangyu Yue, Shilin Zhang, Chunlin Chen, and Zhi Wang, "<a href="https://arxiv.org/abs/2404.10662">Continual Offline Reinforcement Learning via Diffusion-based Dual Generative Replay</a>," <i>arXiv preprint arXiv:2404.10662</i>, 2024. [<a href="https://github.com/NJU-RL/CuGRO">code</a>]
</p></li>
</ul>
<h3>Conferences</h3>
<ul>
<li><p><b>Zhi Wang</b>, Li Zhang, Wenhao Wu, Yuanheng Zhu, Dongbin Zhao, and Chunlin Chen, "<a href="https://arxiv.org/abs/2410.11448">Meta-DT: Offline Meta-RL as Conditional Sequence Modeling with World Model Disentanglement</a>," in <i>Advances of Neural Information Processing Systems (NeurIPS)</i>, 2024. [<a href="https://github.com/NJU-RL/Meta-DT">code</a>] [<a href="paper/2024-NeurIPS-Meta-DT.pdf">pdf</a>]
</p></li>
<li><p>Zican Hu, Zongzhang Zhang, Huaxiong Li, Chunlin Chen, Hongyu Ding, and <b>Zhi Wang*</b>, "<a href="https://arxiv.org/abs/2312.04819">Attention-Guided Contrastive Role Representations for Multi-Agent Reinforcement Learning</a>," in <i>Proceedings of International Conference on Learning Representations (ICLR)</i>, 2024. [<a href="https://github.com/NJU-RL/ACORM">code</a>] [<a href="paper/2024-ICLR-ACORM.pdf">pdf</a>]
</p></li>
<li><p>Junyi Wang, Yuanyang Zhu, <b>Zhi Wang*</b>, Yan Zheng, Jianye Hao, and Chunlin Chen, "<a href="https://arxiv.org/abs/2308.01207">BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel Optimization</a>," in <i>Proceedings of European Conference on Artificial Intelligence (ECAI)</i>, 2023. [<a href="https://github.com/chriswang98sz/BiERL">code</a>]
</p></li>
<li><p><b>Zhi Wang</b>, Wei Bi, Yan Wang, and Xiaojiang Liu, "<a href="https://aaai.org/ojs/index.php/AAAI/article/view/4709">Better fine-tuning via instance weighting for text classification</a>," in <i>Proceedings of AAAI Conference on Artificial Intelligence (AAAI)</i>, 2019, 7241-7248. [<a href="paper/IW_Fit.pdf">pdf</a>] [<a href="paper/IW_Fit_supp.pdf">supp</a>]
</p> </li>
</ul>
<h3>Journals</h3>
<ul>
<li><p>Zichuan Liu, Yuanyang Zhu, <b>Zhi Wang*</b>, Yang Gao, and Chunlin Chen, <a href="">MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning Via Mixing Recurrent Soft Decision Trees</a>," <i>IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)</i>, 2025, DOI:10.1109/TPAMI.2025.3540467. [<a href="">pdf</a>]
</p></li>
<li><p>Jinmei Liu, <b>Zhi Wang*</b>, Chunlin Chen, and Daoyi Dong, <a href="https://ieeexplore.ieee.org/abstract/document/10149182">Efficient Bayesian Policy Reuse With a Scalable Observation Model in Deep Reinforcement Learning</a>," <i>IEEE Transactions on Neural Networks and Learning Systems (TNNLS)</i>, 2024, 35(10): 14797-14809. [<a href="paper/2024-TNNLS-EBPR.pdf">pdf</a>]
</p></li>
<li><p>Donghan Xie, <b>Zhi Wang*</b>, Chunlin Chen, and Daoyi Dong, "<a href="https://ieeexplore.ieee.org/document/10003136/metrics">Depthwise convolution for multi-agent communication with enhanced mean-field approximation</a>," <i>IEEE Transactions on Neural Networks and Learning Systems (TNNLS)</i>, 2024, 35(6): 8557-8569. [<a href="paper/2024-DCCP-TNNLS.pdf">pdf</a>]
</p> </li>
<li><p>Hongyu Ding, Yuanze Tang, Qing Wu, Bo Wang, Chunlin Chen, <b>Zhi Wang*</b>, "<a href="https://www.ieee-jas.net/en/article/doi/10.1109/JAS.2023.123477">Magnetic field-base reward shaping for goal-conditioned reinforcement learning</a>," <i>IEEE-CAA Journal of Automatica Sinica (JAS)</i>, 2023, 10(12): 1-15. [<a href="paper/2023-JAS-MFRS.pdf">pdf</a>] [<a href="https://github.com/Darkness-hy/mfrs">code</a>] [<a href="https://hongyuding.wixsite.com/mfrs">video</a>]
</p></li>
<li><p>Junyi Wang, <b>Zhi Wang*</b>, Huaxiong Li, Chunlin Chen, <a href="http://www.aas.net.cn/cn/article/doi/10.16383/j.aas.c220103?viewType=HTML">Adaptive noise-based evolutionary reinforcement learning with maximum entropy</a>, Acta Automatica Sinica, 2023, 49(1): 54−66. [<a href="paper/AERL_ME.pdf">pdf</a>]
</p> </li>
<li><p><b>Zhi Wang</b>, Chunlin Chen, and Daoyi Dong, "<a href="https://ieeexplore.ieee.org/abstract/document/9777250">A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement Learning</a>," <i>IEEE Transactions on Cybernetics (TCYB)</i>, 2023, 53(12): 7509-7520. [<a href="paper/2022-DPM-LLRL-TCYB-online.pdf">pdf</a>] [<a href="https://github.com/HeyuanMingong/llirl">code</a>]
</p> </li>
<li><p><b>Zhi Wang</b>, Chunlin Chen, and Daoyi Dong, "<a href="https://ieeexplore.ieee.org/abstract/document/9744521">Instance weighted incremental evolution strategies for reinforcement learning in dynamic environments</a>," <i>IEEE Transactions on Neural Networks and Learning Systems (TNNLS)</i>, 2023, 34(12): 9742-9756. [<a href="paper/IWIES.pdf">pdf</a>] [<a href="https://github.com/HeyuanMingong/iwies">code</a>]
</p> </li>
<li><p>Yuanyang Zhu, <b>Zhi Wang*</b>, Chunlin Chen, and Daoyi Dong, "<a href="https://ieeexplore.ieee.org/document/9403986">Rule-based reinforcement learning for efficient robot navigation with space reduction</a>," <i>IEEE-ASME Transactions on Mechatronics (TMECH)</i>, 2022, 27(2): 846-857. [<a href="paper/RuRL.pdf">pdf</a>] [<a href="paper/RuRL_supp.pdf">supp</a>]
</p> </li>
<li><p><b>Zhi Wang</b>, Chunlin Chen, and Daoyi Dong, "<a href="https://ieeexplore.ieee.org/abstract/document/9353402/">Lifelong incremental reinforcement learning with online Bayesian inference</a>," <i>IEEE Transactions on Neural Networks and Learning Systems (TNNLS)</i>, 2022, 33(8): 4003-4016. [<a href="paper/LLIRL.pdf">pdf</a>] [<a href="https://github.com/HeyuanMingong/llirl">code</a>]
</p> </li>
<li><p><b>Zhi Wang</b> and Han-Xiong Li, "<a href="https://ieeexplore.ieee.org/document/8730299">Dissimilarity analysis based multimode modeling for complex distributed parameter systems</a>," <i>IEEE Transactions on Systems, Man, and Cybernetics: Systems (TSYS)</i>, 2021, 51(5): 2789-2797. [<a href="paper/DA_MMM.pdf">pdf</a>]
</p> </li>
<li><p><b>Zhi Wang</b>, Han-Xiong Li, and Chunlin Chen, "<a href="https://ieeexplore.ieee.org/document/8786875">Incremental reinforcement learning in continuous spaces via policy relaxation and importance weighting</a>," <i>IEEE Transactions on Neural Networks and Learning Systems (TNNLS)</i>, 2020, 31(6): 1870-1883. [<a href="paper/IRL_CS.pdf">pdf</a>] [<a href="https://github.com/HeyuanMingong/irl_cs">code</a>]
</p> </li>
<li><p><b>Zhi Wang</b>, Han-Xiong Li, and Chunlin Chen, "<a href="https://ieeexplore.ieee.org/document/8668561">Reinforcement learning based optimal sensor placement for spatiotemporal modeling</a>," <i>IEEE Transactions on Cybernetics (TCYB)</i>, 2020, 50(6): 2861-2871. [<a href="paper/RL_OSP.pdf">pdf</a>]
</p> </li>
<li><p><b>Zhi Wang</b>, Chunlin Chen, Han-Xiong Li, Daoyi Dong, and Tzyh-Jong Tarn, "<a href="https://ieeexplore.ieee.org/document/8642342">Incremental reinforcement learning with prioritized sweeping for dynamic environments</a>," <i>IEEE-ASME Transactions on Mechatronics (TMECH)</i>, 2019, 24(2): 621-632. [<a href="paper/IRL.pdf">pdf</a>] [<a href="https://github.com/HeyuanMingong/irl">code</a>]
</p> </li>
<li><p><b>Zhi Wang</b> and Han-Xiong Li, "<a href="https://ieeexplore.ieee.org/document/8319440">Incremental spatiotemporal learning for online modeling of distributed parameter systems</a>," <i>IEEE Transactions on Systems, Man, and Cybernetics: Systems (TSYS)</i>, 2019, 49(12): 2612-2622. [<a href="paper/IKL.pdf">pdf</a>]
</p> </li>
</ul>
<p><b>Note</b>: *indicates the corresponding author.</p>
</td>
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</table>
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