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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
1142018
Finding robust solutions to dynamic optimization problems
H Fu, B Sendhoff, K Tang, X Yao
Applications of Evolutionary Computation: 16th European Conference …, 2013
482013
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
462014
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
332014
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
242012
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
182014
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
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
152022
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, 2022
122022
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
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
32021
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, 2023
12023
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
12022
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
12022
PARAMETRIZED DEEP Q-NETWORKS LEARNING: PLAYING ONLINE BATTLE ARENA WITH DISCRETE-CONTINUOUS HYBRID ACTION SPACE
J Xiong, Q Wang, Z Yang, P Sun, Y Zheng, L Han, H Fu, X Lian, ...
1
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
2023
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, 2023
2023
Group-oriented Cooperation in Multi-Agent Reinforcement Learning
Y Zang, J He, K Li, H Fu, Q FU, J Xing, J Cheng
2023
Speedup Training Artificial Intelligence for Mahjong via Reward Variance Reduction
J Li, S Wu, H Fu, Q Fu, E Zhao, J Xing
2022 IEEE Conference on Games (CoG), 345-352, 2022
2022
Finding robust solutions against environmental changes
H Fu
University of Birmingham, 2014
2014
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