most citedIndependent RL for Cooperative-Competitive Agents: A Mean-Field Perspective

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IT2025

Distributed Offloading in Multi-Access Edge Computing Systems: A Mean-Field Perspective

Shubham Aggarwal, Muhammad Aneeq uz Zaman, Melih Bastopcu +2

Multi-access edge computing (MEC) technology is a promising solution to assist power-constrained IoT devices by providing additional computing resources for time-sensitive tasks. I…

cs.IT2025

Fully Decentralized Computation Offloading in Priority-Driven Edge Computing Systems

Shubham Aggarwal, Melih Bastopcu, Muhammad Aneeq uz Zaman +3

We develop a novel framework for fully decentralized offloading policy design in multi-access edge computing (MEC) systems. The system comprises power-constrained user equipmen…

math.OC2024

Semantic Communication in Multi-team Dynamic Games: A Mean Field Perspective

Shubham Aggarwal, Muhammad Aneeq uz Zaman, Melih Bastopcu +1

Coordinating communication and control is a key component in the stability and performance of networked multi-agent systems. While single user networked control systems have gained…

cs.MA2024

Robust Cooperative Multi-Agent Reinforcement Learning:A Mean-Field Type Game Perspective

Muhammad Aneeq uz Zaman, Mathieu Laurière, Alec Koppel +1

In this paper, we study the problem of robust cooperative multi-agent reinforcement learning (RL) where a large number of cooperative agents with distributed information aim to lea…

cs.GT2024

Policy Optimization finds Nash Equilibrium in Regularized General-Sum LQ Games

Muhammad Aneeq uz Zaman, Shubham Aggarwal, Melih Bastopcu +1

In this paper, we investigate the impact of introducing relative entropy regularization on the Nash Equilibria (NE) of General-Sum -agent games, revealing the fact that the NE o…

cs.LG2024★ 1 cited

Independent RL for Cooperative-Competitive Agents: A Mean-Field Perspective

Muhammad Aneeq uz Zaman, Alec Koppel, Mathieu Laurière +1

We address in this paper Reinforcement Learning (RL) among agents that are grouped into teams such that there is cooperation within each team but general-sum (non-zero sum) competi…