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Haobo Fu
Haobo Fu
Tencent AI Lab, University of Birmingham
Verified email at tencent.com
Title
Cited by
Cited by
Year
Parametrized deep q-networks learning: Reinforcement learning with discrete-continuous hybrid action space
J Xiong, Q Wang, Z Yang, P Sun, L Han, Y Zheng, H Fu, T Zhang, J Liu, ...
arXiv preprint arXiv:1810.06394, 2018
1962018
Finding robust solutions to dynamic optimization problems
H Fu, B Sendhoff, K Tang, X Yao
Applications of Evolutionary Computation: 16th European Conference …, 2013
612013
Robust optimization over time: Problem difficulties and benchmark problems
H Fu, B Sendhoff, K Tang, X Yao
IEEE Transactions on Evolutionary Computation 19 (5), 731-745, 2014
552014
What are dynamic optimization problems?
H Fu, PR Lewis, B Sendhoff, K Tang, X Yao
2014 IEEE congress on evolutionary computation (CEC), 1550-1557, 2014
352014
Characterizing environmental changes in robust optimization over time
H Fu, B Sendhoff, K Tang, X Yao
2012 IEEE Congress on Evolutionary Computation, 1-8, 2012
282012
Find robust solutions over time by two-layer multi-objective optimization method
Y Guo, M Chen, H Fu, Y Liu
2014 IEEE Congress on Evolutionary Computation (CEC), 1528-1535, 2014
242014
L2E: Learning to exploit your opponent
Z Wu, K Li, H Xu, Y Zang, B An, J Xing
2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022
232022
Actor-critic policy optimization in a large-scale imperfect-information game
H Fu, W Liu, S Wu, Y Wang, T Yang, K Li, J Xing, B Li, B Ma, Q Fu, Y Wei
International Conference on Learning Representations, 2021
232021
Memetic algorithm with heuristic candidate list strategy for capacitated arc routing problem
H Fu, Y Mei, K Tang, Y Zhu
IEEE Congress on Evolutionary Computation, 1-8, 2010
172010
Quality-similar diversity via population based reinforcement learning
S Wu, J Yao, H Fu, Y Tian, C Qian, Y Yang, Q Fu, Y Wei
The Eleventh International Conference on Learning Representations, 2022
112022
Greedy when sure and conservative when uncertain about the opponents
H Fu, Y Tian, H Yu, W Liu, S Wu, J Xiong, Y Wen, K Li, J Xing, Q Fu, ...
International Conference on Machine Learning, 6829-6848, 2022
92022
AutoCFR: learning to design counterfactual regret minimization algorithms
H Xu, K Li, H Fu, Q Fu, J Xing
Proceedings of the AAAI Conference on Artificial Intelligence 36 (5), 5244-5251, 2022
82022
Curriculum-based co-design of morphology and control of voxel-based soft robots
Y Wang, S Wu, H Fu, Q Fu, T Zhang, Y Chang, X Wang
The Eleventh International Conference on Learning Representations, 2022
62022
Automatic grouping for efficient cooperative multi-agent reinforcement learning
Y Zang, J He, K Li, H Fu, Q Fu, J Xing, J Cheng
Advances in Neural Information Processing Systems 36, 2024
52024
Policy space diversity for non-transitive games
J Yao, W Liu, H Fu, Y Yang, S McAleer, Q Fu, W Yang
Advances in Neural Information Processing Systems 36, 2024
52024
Enhance Reasoning for Large Language Models in the Game Werewolf
S Wu, L Zhu, T Yang, S Xu, Q Fu, Y Wei, H Fu
arXiv preprint arXiv:2402.02330, 2024
52024
Dynamic discounted counterfactual regret minimization
H Xu, K Li, H Fu, Q Fu, J Xing, J Cheng
The Twelfth International Conference on Learning Representations, 2024
42024
Sequential cooperative multi-agent reinforcement learning
Y Zang, J He, K Li, H Fu, Q Fu, J Xing
Proceedings of the 2023 International Conference on Autonomous Agents and …, 2023
42023
Combining Tree Search and Action Prediction for State-of-the-Art Performance in DouDiZhu.
Y Zhang, D Yan, B Shi, H Fu, Q Fu, H Su, J Zhu, N Chen
IJCAI, 3413-3419, 2021
42021
A Q-learning based evolutionary algorithm for sequential decision making problems
H Fu, PR Lewis, X Yao
Parallel Problem Solving from Nature (PPSN). VUB AI Lab, 2014
42014
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Articles 1–20