Yifan Zang

Orcid: 0000-0003-4537-384X

According to our database1, Yifan Zang authored at least 11 papers between 2020 and 2024.

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

Timeline

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Links

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Bibliography

2024
Sample Efficient Reinforcement Learning Using Graph-Based Memory Reconstruction.
IEEE Trans. Artif. Intell., February, 2024

Intrinsic Action Tendency Consistency for Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Not All Tasks Are Equally Difficult: Multi-Task Deep Reinforcement Learning with Dynamic Depth Routing.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Not All Tasks Are Equally Difficult: Multi-Task Reinforcement Learning with Dynamic Depth Routing.
CoRR, 2023

Filtered Observations for Model-Based Multi-agent Reinforcement Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Perceptual Video Coding Based on Spatial Masking for Medical Video Communication.
Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition, 2023

Sequential Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022
L2E: Learning to Exploit Your Opponent.
Proceedings of the International Joint Conference on Neural Networks, 2022

Towards a Unified Benchmark for Reinforcement Learning in Sparse Reward Environments.
Proceedings of the Neural Information Processing - 29th International Conference, 2022

2020
Potential Driven Reinforcement Learning for Hard Exploration Tasks.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020


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