16 citations · 58 across the 14 of their papers we have counts for
3 papers · 1 filter
Learning in Nonzero-Sum Stochastic Games with Potentials
David Mguni, Yutong Wu, Yali Du +6
Multi-agent reinforcement learning (MARL) has become effective in tackling discrete cooperative game scenarios. However, MARL has yet to penetrate settings beyond those modelled by…
Coordinating the Crowd: Inducing Desirable Equilibria in Non-Cooperative Systems
David Mguni, Joel Jennings, Sergio Valcarcel Macua +3
Many real-world systems such as taxi systems, traffic networks and smart grids involve self-interested actors that perform individual tasks in a shared environment. However, in suc…
Decentralised Learning in Systems with Many, Many Strategic Agents
David Mguni, Joel Jennings, Enrique Munoz de Cote
Although multi-agent reinforcement learning can tackle systems of strategically interacting entities, it currently fails in scalability and lacks rigorous convergence guarantees. C…