Dr David Mguni

David Mguni

Lecturer in Computer Science

School of Electronic Engineering and Computer Science
Queen Mary University of London
www.qmul.ac.uk/eecs/people/profiles/davidmguni.html
Centre for Multimodal AI
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Research

Multi-agent systems, Reinforcement learning, Game Theory, Statistical learning theory

Interests

My expertise is in multi-agent systems, game theory, and reinforcement learning. My recent works and research interests involve the intersection of game theory and reinforcement learning. My aim is to devise methodologies for intelligent autonomous decision-making systems.

Publications

solid heart iconPublications of specific relevance to the Centre for Multimodal AI

2024

bullet iconDinh LC, Mguni D, Tran-Thanh L, Wang J and Yang Y (2024). A Summary of Online Markov Decision Processes with Non-oblivious Strategic Adversary. International Conference on Autonomous Agents and Multiagent Systems. 
06-05-2024

2023

bullet iconLi H, Huang W, Duan Z, Mguni D, Shao K, Wang J and Deng X (2023). A survey on algorithms for Nash equilibria in finite normal-form games. Computer Science Review, Elsevier 
28-12-2023
bullet iconFeng X, Luo Y, Wang Z, Yang M, Shao K, Mguni D, Du Y and Wang J (2023). ChessGPT: Bridging Policy Learning and Language Modeling. Conference on Neural Information Processing Systems. 
21-09-2023
bullet iconMguni D, Jafferjee T, Wang J, Perez-Nieves N, Song W, Tong F, Taylor M, Yang T, Dai Z, Chen H, Zhu J, Shao K and Yang Y (2023). Learning to Shape Rewards using a Game of Two Partners. Association for the Advancement of Artificial Intelligence. 
26-06-2023
bullet iconMguni D, Chen H, Jafferjee T, Wang J, Yue L, Feng X, McAleer S, Tong F and Yang Y (2023). MANSA: Learning Fast and Slow in Multi-Agent Systems. International Conference on Machine Learning. 
24-04-2023
bullet iconSlumbers O, Mguni D, Blumberg S, McAleer S, Yang Y and Wang J (2023). A game-theoretic framework for managing risk in multi-agent systems. International Conference on Machine Learning. 
24-04-2023
bullet iconMguni D, Sootla A, Ziomek J, Slumbers O, Dai Z, Shao K and Wang J (2023). Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints. International Conference on Learning Representations. 
01-02-2023
bullet iconDinh LC, Mguni D, Tran-Thanh L, Wang J and Yang Y (2023). Online Markov Decision Processes with Non-oblivious Strategic Adversary. Autonomous Agents and Multi-Agent Systems, Springer 
27-01-2023

2022

bullet iconMguni D, Deng X, Li N, Mguni D, Wang J and Yang Y (2022). On the complexity of computing Markov perfect equilibrium in general-sum stochastic games. National Science Review 
22-11-2022
bullet iconDinh LC, McAleer S, Tian Z, Perez-Nieves N, Slumbers O, Mguni D, Wang J, Bou Ammar H and Yang Y (2022). Online double oracle. Transactions on Machine Learning Research 
04-10-2022
bullet iconDai Z, Zhou T, Shao K, Mguni D, Wang B and Hao J (2022). Socially-Attentive Policy Optimization in Multi-Agent Self-Driving System. Conference on Robot Learning. 
10-09-2022
bullet iconMguni D, Chen Y, Deng X, Li C, Wang J, Yan X and Yang Y (2022). On the Convergence of Fictitious Play: A Decomposition Approach. International Joint Conference on Artificial Intelligence. 
03-05-2022
bullet iconMguni D, Sootla A, Cowen-Rivers A, Jafferjee T, Wang Z, Wang J and Bou-Ammar H (2022). SAUTE RL: Almost Surely Safe Reinforcement Learning Using State Augmentation. International Conference on Machine Learning. 
14-02-2022
bullet iconMguni D, Jafferjee T, Wang J, Perez-Nieves N, Slumbers O, Tong F, Li Y, Zhu J and Yang Y (2022). LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning. International Conference on Learning Representations. 
28-01-2022