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ORCIDDavid Mguni
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2020 – today
- 2024
[j3]Hanyu Li
, Wenhan Huang, Zhijian Duan, David Henry Mguni, Kun Shao, Jun Wang, Xiaotie Deng:
A survey on algorithms for Nash equilibria in finite normal-form games. Comput. Sci. Rev. 51: 100613 (2024)- [c16]Le Cong Dinh, David Henry Mguni, Long Tran-Thanh, Jun Wang, Yaodong Yang:
A Summary of Online Markov Decision Processes with Non-oblivious Strategic Adversary. AAMAS 2024: 2830-2832 - [i27]Zhixun Chen, Yali Du, David Mguni:
All Language Models Large and Small. CoRR abs/2402.12061 (2024) - [i26]David Mguni:
Stochastic Games with Minimally Bounded Action Costs. CoRR abs/2407.18010 (2024) - 2023
- [j2]Le Cong Dinh, David Henry Mguni, Long Tran-Thanh, Jun Wang, Yaodong Yang:
Online Markov decision processes with non-oblivious strategic adversary. Auton. Agents Multi Agent Syst. 37(1): 15 (2023) - [c15]David Mguni, Taher Jafferjee, Jianhong Wang, Nicolas Perez Nieves, Wenbin Song, Feifei Tong, Matthew E. Taylor, Tianpei Yang, Zipeng Dai, Hui Chen, Jiangcheng Zhu, Kun Shao, Jun Wang, Yaodong Yang:
Learning to Shape Rewards Using a Game of Two Partners. AAAI 2023: 11604-11612 - [c14]David Henry Mguni, Aivar Sootla, Juliusz Ziomek, Oliver Slumbers, Zipeng Dai, Kun Shao, Jun Wang:
Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints. ICLR 2023 - [c13]David Henry Mguni, Haojun Chen, Taher Jafferjee, Jianhong Wang, Longfei Yue, Xidong Feng, Stephen Marcus McAleer, Feifei Tong, Jun Wang, Yaodong Yang:
MANSA: Learning Fast and Slow in Multi-Agent Systems. ICML 2023: 24631-24658 - [c12]Oliver Slumbers, David Henry Mguni, Stefano B. Blumberg, Stephen Marcus McAleer, Yaodong Yang, Jun Wang:
A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems. ICML 2023: 32059-32087 - [c11]Xidong Feng, Yicheng Luo, Ziyan Wang, Hongrui Tang, Mengyue Yang, Kun Shao, David Mguni, Yali Du, Jun Wang:
ChessGPT: Bridging Policy Learning and Language Modeling. NeurIPS 2023 - [i25]Lukas Schäfer, Oliver Slumbers, Stephen McAleer, Yali Du, Stefano V. Albrecht, David Mguni:
Ensemble Value Functions for Efficient Exploration in Multi-Agent Reinforcement Learning. CoRR abs/2302.03439 (2023) - [i24]David Mguni, Taher Jafferjee, Haojun Chen, Jianhong Wang, Long Fei, Xidong Feng, Stephen McAleer, Feifei Tong, Jun Wang, Yaodong Yang:
MANSA: Learning Fast and Slow in Multi-Agent Systems. CoRR abs/2302.05910 (2023) - [i23]Xidong Feng, Yicheng Luo, Ziyan Wang, Hongrui Tang, Mengyue Yang, Kun Shao, David Mguni, Yali Du, Jun Wang:
ChessGPT: Bridging Policy Learning and Language Modeling. CoRR abs/2306.09200 (2023) - [i22]Xue Yan, Yan Song, Xinyu Cui, Filippos Christianos, Haifeng Zhang, David Henry Mguni, Jun Wang:
Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models. CoRR abs/2310.18127 (2023) - [i21]Hanyu Li, Wenhan Huang, Zhijian Duan, David Henry Mguni, Kun Shao, Jun Wang, Xiaotie Deng:
A survey on algorithms for Nash equilibria in finite normal-form games. CoRR abs/2312.11063 (2023) - 2022
- [j1]Le Cong Dinh, Stephen Marcus McAleer, Zheng Tian, Nicolas Perez Nieves, Oliver Slumbers, David Henry Mguni, Jun Wang, Haitham Bou-Ammar, Yaodong Yang:
Online Double Oracle. Trans. Mach. Learn. Res. 2022 (2022) - [c10]Zipeng Dai, Tianze Zhou, Kun Shao, David Henry Mguni, Bin Wang, Jianye Hao:
Socially-Attentive Policy Optimization in Multi-Agent Self-Driving System. CoRL 2022: 946-955 - [c9]David Henry Mguni, Taher Jafferjee, Jianhong Wang, Nicolas Perez Nieves, Oliver Slumbers, Feifei Tong, Yang Li, Jiangcheng Zhu, Yaodong Yang, Jun Wang:
LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning. ICLR 2022 - [c8]Aivar Sootla, Alexander I. Cowen-Rivers, Taher Jafferjee, Ziyan Wang, David Henry Mguni, Jun Wang, Haitham Ammar:
Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation. ICML 2022: 20423-20443 - [c7]Yurong Chen, Xiaotie Deng, Chenchen Li, David Mguni, Jun Wang, Xiang Yan, Yaodong Yang:
On the Convergence of Fictitious Play: A Decomposition Approach. IJCAI 2022: 179-185 - [i20]Aivar Sootla, Alexander I. Cowen-Rivers, Taher Jafferjee, Ziyan Wang, David Mguni, Jun Wang, Haitham Bou-Ammar:
SAUTE RL: Almost Surely Safe Reinforcement Learning Using State Augmentation. CoRR abs/2202.06558 (2022) - [i19]Yurong Chen, Xiaotie Deng, Chenchen Li, David Mguni, Jun Wang, Xiang Yan, Yaodong Yang:
On the Convergence of Fictitious Play: A Decomposition Approach. CoRR abs/2205.01469 (2022) - [i18]Changmin Yu, David Mguni, Dong Li, Aivar Sootla, Jun Wang, Neil Burgess:
SEREN: Knowing When to Explore and When to Exploit. CoRR abs/2205.15064 (2022) - [i17]Oliver Slumbers, David Henry Mguni, Stephen McAleer, Jun Wang, Yaodong Yang:
Learning Risk-Averse Equilibria in Multi-Agent Systems. CoRR abs/2205.15434 (2022) - [i16]David Mguni, Aivar Sootla, Juliusz Krysztof Ziomek, Oliver Slumbers, Zipeng Dai, Kun Shao, Jun Wang:
Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints. CoRR abs/2205.15953 (2022) - [i15]Taher Jafferjee, Juliusz Krysztof Ziomek, Tianpei Yang, Zipeng Dai, Jianhong Wang, Matthew E. Taylor, Kun Shao, Jun Wang, David Mguni:
Semi-Centralised Multi-Agent Reinforcement Learning with Policy-Embedded Training. CoRR abs/2209.01054 (2022) - 2021
- [c6]David Henry Mguni, Yutong Wu, Yali Du, Yaodong Yang, Ziyi Wang, Minne Li, Ying Wen, Joel Jennings, Jun Wang:
Learning in Nonzero-Sum Stochastic Games with Potentials. ICML 2021: 7688-7699 - [c5]Nicolas Perez Nieves, Yaodong Yang, Oliver Slumbers, David Henry Mguni, Ying Wen, Jun Wang:
Modelling Behavioural Diversity for Learning in Open-Ended Games. ICML 2021: 8514-8524 - [c4]Jakub Grudzien Kuba, Muning Wen, Linghui Meng, Shangding Gu, Haifeng Zhang, David Mguni, Jun Wang, Yaodong Yang:
Settling the Variance of Multi-Agent Policy Gradients. NeurIPS 2021: 13458-13470 - [i14]Le Cong Dinh, Yaodong Yang, Zheng Tian, Nicolas Perez Nieves, Oliver Slumbers, David Henry Mguni, Haitham Bou-Ammar, Jun Wang:
Online Double Oracle. CoRR abs/2103.07780 (2021) - [i13]Nicolas Perez Nieves, Yaodong Yang, Oliver Slumbers, David Henry Mguni, Jun Wang:
Modelling Behavioural Diversity for Learning in Open-Ended Games. CoRR abs/2103.07927 (2021) - [i12]David Mguni, Jianhong Wang, Taher Jafferjee, Nicolas Perez Nieves, Wenbin Song, Yaodong Yang, Feifei Tong, Hui Chen, Jiangcheng Zhu, Yali Du, Jun Wang:
Learning to Shape Rewards using a Game of Switching Controls. CoRR abs/2103.09159 (2021) - [i11]David Mguni, Yutong Wu, Yali Du, Yaodong Yang, Ziyi Wang, Minne Li, Ying Wen, Joel Jennings, Jun Wang:
Learning in Nonzero-Sum Stochastic Games with Potentials. CoRR abs/2103.09284 (2021) - [i10]Jakub Grudzien Kuba, Muning Wen, Yaodong Yang, Linghui Meng, Shangding Gu, Haifeng Zhang, David Henry Mguni, Jun Wang:
Settling the Variance of Multi-Agent Policy Gradients. CoRR abs/2108.08612 (2021) - [i9]Xiaotie Deng, Yuhao Li, David Henry Mguni, Jun Wang, Yaodong Yang:
On the Complexity of Computing Markov Perfect Equilibrium in General-Sum Stochastic Games. CoRR abs/2109.01795 (2021) - [i8]Le Cong Dinh, David Henry Mguni, Long Tran-Thanh, Jun Wang, Yaodong Yang:
Online Markov Decision Processes with Non-oblivious Strategic Adversary. CoRR abs/2110.03604 (2021) - [i7]David Mguni, Joel Jennings, Taher Jafferjee, Aivar Sootla, Yaodong Yang, Changmin Yu, Usman Islam, Ziyan Wang, Jun Wang:
DESTA: A Framework for Safe Reinforcement Learning with Markov Games of Intervention. CoRR abs/2110.14468 (2021) - [i6]David Henry Mguni, Taher Jafferjee, Jianhong Wang, Nicolas Perez Nieves, Oliver Slumbers, Feifei Tong, Yang Li, Jiangcheng Zhu, Yaodong Yang, Jun Wang:
LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning. CoRR abs/2112.02618 (2021) - [i5]Xiaotie Deng, Yuhao Li, David Mguni, Jun Wang, Yaodong Yang:
On the Complexity of Computing Markov Perfect Equilibrium in General-Sum Stochastic Games. Electron. Colloquium Comput. Complex. TR21 (2021) - 2020
- [c3]Yaodong Yang, Ying Wen, Jun Wang, Liheng Chen, Kun Shao, David Mguni, Weinan Zhang:
Multi-Agent Determinantal Q-Learning. ICML 2020: 10757-10766 - [i4]Yaodong Yang, Ying Wen, Liheng Chen, Jun Wang, Kun Shao, David Mguni, Weinan Zhang:
Multi-Agent Determinantal Q-Learning. CoRR abs/2006.01482 (2020)
2010 – 2019
- 2019
- [c2]David Mguni, Joel Jennings, Emilio Sison, Sergio Valcarcel Macua, Sofia Ceppi, Enrique Munoz de Cote:
Coordinating the Crowd: Inducing Desirable Equilibria in Non-Cooperative Systems. AAMAS 2019: 386-394 - [i3]David Mguni, Joel Jennings, Sergio Valcarcel Macua, Emilio Sison, Sofia Ceppi, Enrique Munoz de Cote:
Coordinating the Crowd: Inducing Desirable Equilibria in Non-Cooperative Systems. CoRR abs/1901.10923 (2019) - [i2]David Mguni:
Cutting Your Losses: Learning Fault-Tolerant Control and Optimal Stopping under Adverse Risk. CoRR abs/1902.05045 (2019) - 2018
- [c1]David Mguni, Joel Jennings, Enrique Munoz de Cote:
Decentralised Learning in Systems With Many, Many Strategic Agents. AAAI 2018: 4686-4693 - [i1]David Mguni, Joel Jennings, Enrique Munoz de Cote:
Decentralised Learning in Systems with Many, Many Strategic Agents. CoRR abs/1803.05028 (2018)
Coauthor Index
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