受强制性开放获取政策约束的文章 - QIANG FU了解详情
可在其他位置公开访问的文章：12 篇
Which heroes to pick? learning to draft in moba games with neural networks and tree search
S Chen, M Zhu, D Ye, W Zhang, Q Fu, W Yang
IEEE Transactions on Games 13 (4), 410-421, 2021
强制性开放获取政策： 国家自然科学基金委员会
Honor of kings arena: an environment for generalization in competitive reinforcement learning
H Wei, J Chen, X Ji, H Qin, M Deng, S Li, L Wang, W Zhang, Y Yu, L Linc, ...
Advances in Neural Information Processing Systems 35, 11881-11892, 2022
强制性开放获取政策： 国家自然科学基金委员会
Future-conditioned unsupervised pretraining for decision transformer
Z Xie, Z Lin, D Ye, Q Fu, Y Wei, S Li
International Conference on Machine Learning, 38187-38203, 2023
强制性开放获取政策： 国家自然科学基金委员会
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
强制性开放获取政策： 中国科学院, 国家自然科学基金委员会
Deep reinforcement learning task assignment based on domain knowledge
J Liu, G Wang, X Guo, S Wang, Q Fu
IEEE Access 10, 114402-114413, 2022
强制性开放获取政策： 国家自然科学基金委员会
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
强制性开放获取政策： 中国科学院, 国家自然科学基金委员会
Dynamics-adaptive continual reinforcement learning via progressive contextualization
T Zhang, Z Lin, Y Wang, D Ye, Q Fu, W Yang, X Wang, B Liang, B Yuan, ...
IEEE Transactions on Neural Networks and Learning Systems, 2023
强制性开放获取政策： Australian Research Council
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
强制性开放获取政策： 国家自然科学基金委员会
PreCo: Enhancing Generalization in Co-Design of Modular Soft Robots via Brain-Body Pre-Training
Y Wang, S Wu, T Zhang, Y Chang, H Fu, Q Fu, X Wang
Conference on Robot Learning, 478-498, 2023
强制性开放获取政策： 国家自然科学基金委员会
Multi-objective Optimization-based Selection for Quality-Diversity by Non-surrounded-dominated Sorting
RJ Wang, K Xue, H Shang, C Qian, H Fu, Q Fu
ijcai, 2023
强制性开放获取政策： 国家自然科学基金委员会
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
强制性开放获取政策： 中国科学院, 国家自然科学基金委员会
Towards Offline Opponent Modeling with In-context Learning
Y Jing, K Li, B Liu, Y Zang, H Fu, Q FU, J Xing, J Cheng
The Twelfth International Conference on Learning Representations, 2023
强制性开放获取政策： 国家自然科学基金委员会
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