Yang Li

Affiliations:
  • Shanghai University, School of Computer Engineering and Science, Shanghai, China


According to our database1, Yang Li authored at least 13 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Hierarchical relationship modeling in multi-agent reinforcement learning for mixed cooperative-competitive environments.
Inf. Fusion, 2024

FGeo-HyperGNet: Geometry Problem Solving Integrating Formal Symbolic System and Hypergraph Neural Network.
CoRR, 2024

2023
FormalGeo: The First Step Toward Human-like IMO-level Geometric Automated Reasoning.
CoRR, 2023

2022
ET-HF: A novel information sharing model to improve multi-agent cooperation.
Knowl. Based Syst., 2022

USVs-Sim: A general simulation platform for unmanned surface vessels autonomous learning.
Concurr. Comput. Pract. Exp., 2022

Fully Parameterized Dueling Mixing Distributional Q-Leaning for Multi-Agent Cooperation.
Proceedings of the 34th IEEE International Conference on Tools with Artificial Intelligence, 2022

2021
Learning adversarial policy in multiple scenes environment via multi-agent reinforcement learning.
Connect. Sci., 2021

Unmanned surface vessel obstacle avoidance with prior knowledge-based reward shaping.
Concurr. Comput. Pract. Exp., 2021

Learning Heterogeneous Strategies via Graph-based Multi-agent Reinforcement Learning.
Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

2020
SEM: Adaptive Staged Experience Access Mechanism for Reinforcement Learning.
Proceedings of the 32nd IEEE International Conference on Tools with Artificial Intelligence, 2020

Cooperative Multi-Agent Reinforcement Learning with Hierarchical Relation Graph under Partial Observability.
Proceedings of the 32nd IEEE International Conference on Tools with Artificial Intelligence, 2020

2019
Proximal Policy Optimization with Mixed Distributed Training.
CoRR, 2019

Proximal Policy Optimization with Mixed Distributed Training.
Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019


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