Work

Hierarchical Policy Optimization for Cooperative Multi-Agent Reinforcement Learning

Year: 2024

Type: conference-paper

Source: Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics

DOI: 10.1109/smc54092.2024.10831538

Authors: Shunfan He, Ronghao Zheng, Senlin Zhang, Meiqin Liu

Institutions: Zhejiang University, Xi'an Jiaotong University

Language: English

Topic: Reinforcement Learning in Robotics

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funders: National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province

Awards: G1502531386, 复杂环境下跨域无人系统协同技术研究

OpenAlex ID: W4406612934

FWCI:

Cites: 17

Cited by:

Related to: 10