Zobrazeno 1 - 10
of 751
pro vyhledávání: '"Wang, Jianhao"'
Recent offline meta-reinforcement learning (meta-RL) methods typically utilize task-dependent behavior policies (e.g., training RL agents on each individual task) to collect a multi-task dataset. However, these methods always require extra informatio
Externí odkaz:
http://arxiv.org/abs/2305.19529
Decentralized execution is one core demand in cooperative multi-agent reinforcement learning (MARL). Recently, most popular MARL algorithms have adopted decentralized policies to enable decentralized execution and use gradient descent as their optimi
Externí odkaz:
http://arxiv.org/abs/2207.11143
Autor:
Chen, Xi, Ghadirzadeh, Ali, Yu, Tianhe, Gao, Yuan, Wang, Jianhao, Li, Wenzhe, Liang, Bin, Finn, Chelsea, Zhang, Chongjie
Offline reinforcement learning methods hold the promise of learning policies from pre-collected datasets without the need to query the environment for new transitions. This setting is particularly well-suited for continuous control robotic applicatio
Externí odkaz:
http://arxiv.org/abs/2203.08949
Autor:
Zhao, Donghui, Deng, Yunhao, Shi, Junyi, Ni, Xinye, Li, Chaoqing, Bai, Yang, Xuan, Yang, Wang, Jianhao
Publikováno v:
In International Journal of Biological Macromolecules September 2024 276 Part 2
Publikováno v:
In Biomedicine & Pharmacotherapy August 2024 177
Autor:
Shen, Xinyue, Zhao, Donghui, Shi, Junyi, Li, Chaoqing, Bai, Yang, Qiu, Lin, Xuan, Yang, Wang, Jianhao
Publikováno v:
In International Journal of Biological Macromolecules August 2024 274 Part 2
Autor:
Pan, Jiaoyang, Ge, Qiqi, Wang, Beibei, Chen, Jiayi, Hu, Huaanzi, Qiu, Lin, Wang, Jianhao, Wang, Cheng, Xu, Hongbin
Publikováno v:
In Journal of Drug Delivery Science and Technology August 2024 97
Publikováno v:
In Materials Science in Semiconductor Processing January 2025 185
Coordination graph is a promising approach to model agent collaboration in multi-agent reinforcement learning. It conducts a graph-based value factorization and induces explicit coordination among agents to complete complicated tasks. However, one cr
Externí odkaz:
http://arxiv.org/abs/2112.03547
Autor:
Zheng, Lulu, Chen, Jiarui, Wang, Jianhao, He, Jiamin, Hu, Yujing, Chen, Yingfeng, Fan, Changjie, Gao, Yang, Zhang, Chongjie
Efficient exploration in deep cooperative multi-agent reinforcement learning (MARL) still remains challenging in complex coordination problems. In this paper, we introduce a novel Episodic Multi-agent reinforcement learning with Curiosity-driven expl
Externí odkaz:
http://arxiv.org/abs/2111.11032