1 code implementation • 31 May 2024 • Siyi Hu, Diego Martin Arroyo, Stephanie Debats, Fabian Manhardt, Luca Carlone, Federico Tombari
Realistic conditional 3D scene synthesis significantly enhances and accelerates the creation of virtual environments, which can also provide extensive training data for computer vision and robotics research among other applications.
no code implementations • 30 Aug 2023 • Li He, Siyi Hu, Ailun Pei
The Internet and social media have altered how individuals access news in the age of instantaneous information distribution.
no code implementations • 22 Aug 2023 • Ceyao Zhang, Kaijie Yang, Siyi Hu, ZiHao Wang, Guanghe Li, Yihang Sun, Cheng Zhang, Zhaowei Zhang, Anji Liu, Song-Chun Zhu, Xiaojun Chang, Junge Zhang, Feng Yin, Yitao Liang, Yaodong Yang
Building agents with adaptive behavior in cooperative tasks stands as a paramount goal in the realm of multi-agent systems.
1 code implementation • 19 Jun 2023 • Jiarong Liu, Yifan Zhong, Siyi Hu, Haobo Fu, Qiang Fu, Xiaojun Chang, Yaodong Yang
We embed cooperative MARL problems into probabilistic graphical models, from which we derive the maximum entropy (MaxEnt) objective for MARL.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 19 Apr 2023 • Yifan Zhong, Jakub Grudzien Kuba, Xidong Feng, Siyi Hu, Jiaming Ji, Yaodong Yang
The necessity for cooperation among intelligent machines has popularised cooperative multi-agent reinforcement learning (MARL) in AI research.
1 code implementation • 11 Oct 2022 • Siyi Hu, Yifan Zhong, Minquan Gao, Weixun Wang, Hao Dong, Xiaodan Liang, Zhihui Li, Xiaojun Chang, Yaodong Yang
A significant challenge facing researchers in the area of multi-agent reinforcement learning (MARL) pertains to the identification of a library that can offer fast and compatible development for multi-agent tasks and algorithm combinations, while obviating the need to consider compatibility issues.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 12 Sep 2022 • William Chen, Siyi Hu, Rajat Talak, Luca Carlone
Abstract semantic 3D scene understanding is a problem of critical importance in robotics.
no code implementations • 9 Jun 2022 • William Chen, Siyi Hu, Rajat Talak, Luca Carlone
Semantic 3D scene understanding is a problem of critical importance in robotics.
no code implementations • 1 Jun 2022 • Siyi Hu, Chuanlong Xie, Xiaodan Liang, Xiaojun Chang
In this study, we quantify the agent's behavior difference and build its relationship with the policy performance via {\bf Role Diversity}, a metric to measure the characteristics of MARL tasks.
no code implementations • 29 Sep 2021 • Siyi Hu, Chuanlong Xie, Xiaodan Liang, Xiaojun Chang
In addition, role diversity can help to find a better training strategy and increase performance in cooperative MARL.
no code implementations • NeurIPS 2021 • Rajat Talak, Siyi Hu, Lisa Peng, Luca Carlone
We also prove that the number of parameters needed to achieve an $\epsilon$-approximation of the distribution function is exponential in the treewidth of the input graph, but linear in its size.
1 code implementation • 20 Jan 2021 • Siyi Hu, Fengda Zhu, Xiaojun Chang, Xiaodan Liang
Recent advances in multi-agent reinforcement learning have been largely limited in training one model from scratch for every new task.
no code implementations • ICLR 2021 • Siyi Hu, Fengda Zhu, Xiaojun Chang, Xiaodan Liang
Recent advances in multi-agent reinforcement learning have been largely limited in training one model from scratch for every new task.
no code implementations • 23 Jun 2020 • Siyi Hu, Xiaojun Chang
In this paper, we focus on the task of multi-view multi-source geo-localization, which serves as an important auxiliary method of GPS positioning by matching drone-view image and satellite-view image with pre-annotated GPS tag.
1 code implementation • 27 Oct 2018 • Siyi Hu, Luca Carlone
We show that this approach, named Fast Unconstrained SEmidefinite Solver (FUSES), can solve large problems in milliseconds.
1 code implementation • 27 Oct 2018 • Pierre-Yves Lajoie, Siyi Hu, Giovanni Beltrame, Luca Carlone
Perceptual aliasing is one of the main causes of failure for Simultaneous Localization and Mapping (SLAM) systems operating in the wild.
Robotics 65K05, 62F10, 68T40, 68W40, 68W25, I.2.9; G.1.6