1 code implementation • 18 Apr 2024 • Haoyuan Jiang, Ziyue Li, Hua Wei, Xuantang Xiong, Jingqing Ruan, Jiaming Lu, Hangyu Mao, Rui Zhao
The effectiveness of traffic light control has been significantly improved by current reinforcement learning-based approaches via better cooperation among multiple traffic lights.
1 code implementation • 22 Dec 2023 • Jiaming Lu, Jingqing Ruan, Haoyuan Jiang, Ziyue Li, Hangyu Mao, Rui Zhao
Furthermore, we implement a scenario-shared Co-Train module to facilitate the learning of generalizable dynamics information across different scenarios.
no code implementations • 26 Oct 2023 • Henry H. H. Chen, Jiaming Lu
The prevailing principle of "Optimism in the Face of Uncertainty" advocates for the incorporation of an exploration bonus, generally assumed to be proportional to the inverse square root of the visit count ($1/\sqrt{n}$), where $n$ is the number of visits to a particular state-action pair.
no code implementations • 11 Aug 2023 • Yiyang Cai, Jiaming Lu, Jiewen Wang, Shuang Liang
UACTN decouples the representation learning of sketches and 3D shapes into two separate tasks: classification-based sketch uncertainty learning and 3D shape feature transfer.
no code implementations • 1 Jun 2016 • Zhe Zhu, Jiaming Lu, Minxuan Wang, Song-Hai Zhang, Ralph Martin, Hantao Liu, Shi-Min Hu
In this paper, we investigate 6 popular blending algorithms---feather blending, multi-band blending, modified Poisson blending, mean value coordinate blending, multi-spline blending and convolution pyramid blending.