David Mguni

According to our database, David Mguni authored at least 32 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

All Language Models Large and Small.

Zhixun Chen, Yali Du, David Mguni

CoRR, 2024

2023

Online Markov decision processes with non-oblivious strategic adversary.

Le Cong Dinh, David Henry Mguni, Long Tran-Thanh, Jun Wang, Yaodong Yang

Auton. Agents Multi Agent Syst., June, 2023

A survey on algorithms for Nash equilibria in finite normal-form games.

Hanyu Li, Wenhan Huang, Zhijian Duan, David Henry Mguni, Kun Shao, Jun Wang, Xiaotie Deng

CoRR, 2023

Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models.

Xue Yan, Yan Song, Xinyu Cui, Filippos Christianos, Haifeng Zhang, David Henry Mguni, Jun Wang

CoRR, 2023

ChessGPT: Bridging Policy Learning and Language Modeling.

Xidong Feng, Yicheng Luo, Ziyan Wang, Hongrui Tang, Mengyue Yang, Kun Shao, David Mguni, Yali Du, Jun Wang

CoRR, 2023

MANSA: Learning Fast and Slow in Multi-Agent Systems.

David Mguni, Taher Jafferjee, Haojun Chen, Jianhong Wang, Long Fei, Xidong Feng, Stephen McAleer, Feifei Tong, Jun Wang, Yaodong Yang

CoRR, 2023

Ensemble Value Functions for Efficient Exploration in Multi-Agent Reinforcement Learning.

Lukas Schäfer, Oliver Slumbers, Stephen McAleer, Yali Du, Stefano V. Albrecht, David Mguni

CoRR, 2023

ChessGPT: Bridging Policy Learning and Language Modeling.

Xidong Feng, Yicheng Luo, Ziyan Wang, Hongrui Tang, Mengyue Yang, Kun Shao, David Mguni, Yali Du, Jun Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems.

Oliver Slumbers, David Henry Mguni, Stefano B. Blumberg, Stephen Marcus McAleer, Yaodong Yang, Jun Wang

Proceedings of the International Conference on Machine Learning, 2023

MANSA: Learning Fast and Slow in Multi-Agent Systems.

David Henry Mguni, Haojun Chen, Taher Jafferjee, Jianhong Wang, Longfei Yue, Xidong Feng, Stephen Marcus McAleer, Feifei Tong, Jun Wang, Yaodong Yang

Proceedings of the International Conference on Machine Learning, 2023

Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints.

David Henry Mguni, Aivar Sootla, Juliusz Ziomek, Oliver Slumbers, Zipeng Dai, Kun Shao, Jun Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning to Shape Rewards Using a Game of Two Partners.

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

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Online Double Oracle.

Le Cong Dinh, Stephen Marcus McAleer, Zheng Tian, Nicolas Perez Nieves, Oliver Slumbers, David Henry Mguni, Jun Wang, Haitham Bou-Ammar, Yaodong Yang

Trans. Mach. Learn. Res., 2022

Semi-Centralised Multi-Agent Reinforcement Learning with Policy-Embedded Training.

Taher Jafferjee, Juliusz Krysztof Ziomek, Tianpei Yang, Zipeng Dai, Jianhong Wang, Matthew E. Taylor, Kun Shao, Jun Wang, David Mguni

CoRR, 2022

Learning Risk-Averse Equilibria in Multi-Agent Systems.

Oliver Slumbers, David Henry Mguni, Stephen McAleer, Jun Wang, Yaodong Yang

CoRR, 2022

SEREN: Knowing When to Explore and When to Exploit.

Changmin Yu, David Mguni, Dong Li, Aivar Sootla, Jun Wang, Neil Burgess

CoRR, 2022

On the Convergence of Fictitious Play: A Decomposition Approach.

Yurong Chen, Xiaotie Deng, Chenchen Li, David Mguni, Jun Wang, Xiang Yan, Yaodong Yang

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation.

Aivar Sootla, Alexander I. Cowen-Rivers, Taher Jafferjee, Ziyan Wang, David Henry Mguni, Jun Wang, Haitham Ammar

Proceedings of the International Conference on Machine Learning, 2022

LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning.

David Henry Mguni, Taher Jafferjee, Jianhong Wang, Nicolas Perez Nieves, Oliver Slumbers, Feifei Tong, Yang Li, Jiangcheng Zhu, Yaodong Yang, Jun Wang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Socially-Attentive Policy Optimization in Multi-Agent Self-Driving System.

Zipeng Dai, Tianze Zhou, Kun Shao, David Henry Mguni, Bin Wang, Jianye Hao

Proceedings of the Conference on Robot Learning, 2022

2021

On the Complexity of Computing Markov Perfect Equilibrium in General-Sum Stochastic Games.

Xiaotie Deng, Yuhao Li, David Mguni, Jun Wang, Yaodong Yang

Electron. Colloquium Comput. Complex., 2021

DESTA: A Framework for Safe Reinforcement Learning with Markov Games of Intervention.

David Mguni, Joel Jennings, Taher Jafferjee, Aivar Sootla, Yaodong Yang, Changmin Yu, Usman Islam, Ziyan Wang, Jun Wang

CoRR, 2021

Learning to Shape Rewards using a Game of Switching Controls.

David Mguni, Jianhong Wang, Taher Jafferjee, Nicolas Perez Nieves, Wenbin Song, Yaodong Yang, Feifei Tong, Hui Chen, Jiangcheng Zhu, Yali Du, Jun Wang

CoRR, 2021

Modelling Behavioural Diversity for Learning in Open-Ended Games.

Nicolas Perez Nieves, Yaodong Yang, Oliver Slumbers, David Henry Mguni, Jun Wang

CoRR, 2021

Online Double Oracle.

Le Cong Dinh, Yaodong Yang, Zheng Tian, Nicolas Perez Nieves, Oliver Slumbers, David Henry Mguni, Haitham Bou-Ammar, Jun Wang

CoRR, 2021

Settling the Variance of Multi-Agent Policy Gradients.

Jakub Grudzien Kuba, Muning Wen, Linghui Meng, Shangding Gu, Haifeng Zhang, David Mguni, Jun Wang, Yaodong Yang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Modelling Behavioural Diversity for Learning in Open-Ended Games.

Nicolas Perez Nieves, Yaodong Yang, Oliver Slumbers, David Henry Mguni, Ying Wen, Jun Wang

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning in Nonzero-Sum Stochastic Games with Potentials.

David Henry Mguni, Yutong Wu, Yali Du, Yaodong Yang, Ziyi Wang, Minne Li, Ying Wen, Joel Jennings, Jun Wang

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Multi-Agent Determinantal Q-Learning.

Yaodong Yang, Ying Wen, Jun Wang, Liheng Chen, Kun Shao, David Mguni, Weinan Zhang

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Cutting Your Losses: Learning Fault-Tolerant Control and Optimal Stopping under Adverse Risk.

David Mguni

CoRR, 2019

Coordinating the Crowd: Inducing Desirable Equilibria in Non-Cooperative Systems.

David Mguni, Joel Jennings, Emilio Sison, Sergio Valcarcel Macua, Sofia Ceppi, Enrique Munoz de Cote

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

Decentralised Learning in Systems With Many, Many Strategic Agents.

David Mguni, Joel Jennings, Enrique Munoz de Cote

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018