Hongda Jia

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 10

Top Topics

Collision Avoidance

Exploration Exploitation

Reinforcement Learning

Top Venues

IEEE Robotics Autom. Lett.

SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI

Publications

Hongda Jia, Zijian Gao, Cheng Yang, Bo Ding, Yuanzhao Zhai, Huaimin Wang
C3F: Constant Collaboration and Communication Framework for Graph-Representation Dynamic Multi-Robotic Systems. IEEE Robotics Autom. Lett. 9 (1) (2024)
Zijian Gao, Kele Xu, Hongda Jia, Tianjiao Wan, Bo Ding, Dawei Feng, Xinjun Mao, Huaimin Wang
Complementary Learning System Based Intrinsic Reward in Reinforcement Learning. ICASSP (2023)
Hongda Jia, Yong Zhao, Yuanzhao Zhai, Bo Ding, Huaimin Wang, Qingtong Wu
CRMRL: Collaborative Relationship Meta Reinforcement Learning for Effectively Adapting to Type Changes in Multi-Robotic System. IEEE Robotics Autom. Lett. 7 (4) (2022)
Zijian Gao, Kele Xu, Bo Ding, Huaimin Wang, Yiying Li, Hongda Jia
KnowSR: Knowledge Sharing among Homogeneous Agents in Multi-agent Reinforcement Learning. CoRR (2021)
Yuanzhao Zhai, Bo Ding, Xuan Liu, Hongda Jia, Yong Zhao, Jie Luo
Decentralized Multi-Robot Collision Avoidance in Complex Scenarios With Selective Communication. IEEE Robotics Autom. Lett. 6 (4) (2021)
Zijian Gao, Kele Xu, Bo Ding, Huaimin Wang, Yiying Li, Hongda Jia
KnowRU: Knowledge Reusing via Knowledge Distillation in Multi-agent Reinforcement Learning. CoRR (2021)
Xudong Gong, Hongda Jia, Xing Zhou, Dawei Feng, Bo Ding, Jie Xu
Improving Policy Generalization for Teacher-Student Reinforcement Learning. KSEM (2) (2020)
Dingjie He, Dawei Feng, Hongda Jia, Hui Liu
Decentralized Exploration of a Structured Environment Based on Multi-agent Deep Reinforcement Learning. ICPADS (2020)
Hongda Jia, Bo Ding, Huaimin Wang, Xudong Gong, Xing Zhou
Fast Adaptation via Meta Learning in Multi-agent Cooperative Tasks. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI (2019)
Xudong Gong, Bo Ding, Jie Xu, Huaimin Wang, Xing Zhou, Hongda Jia
Synchronous n-Step Method for Independent Q-Learning in Multi-Agent Deep Reinforcement Learning. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI (2019)