68 citations · 265 across the 47 of their papers we have counts for
5 papers · 1 filter
On the Near-Optimality of Local Policies in Large Cooperative Multi-Agent Reinforcement Learning
Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri
We show that in a cooperative -agent network, one can design locally executable policies for the agents such that the resulting discounted sum of average rewards (value) well ap…
Mean-Field Approximation of Cooperative Constrained Multi-Agent Reinforcement Learning (CMARL)
Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri
Mean-Field Control (MFC) has recently been proven to be a scalable tool to approximately solve large-scale multi-agent reinforcement learning (MARL) problems. However, these studie…
Spatial Structure of City Population Growth
Sandro M. Reia, P. Suresh C. Rao, Marc Barthelemy +1
We show here that population growth, resolved at the county level, is spatially heterogeneous both among and within the U.S. metropolitan statistical areas. Our analysis of data fo…
Can Mean Field Control (MFC) Approximate Cooperative Multi Agent Reinforcement Learning (MARL) with Non-Uniform Interaction?
Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri
Mean-Field Control (MFC) is a powerful tool to solve Multi-Agent Reinforcement Learning (MARL) problems. Recent studies have shown that MFC can well-approximate MARL when the popul…
Deep Learning based Coverage and Rate Manifold Estimation in Cellular Networks
Washim Uddin Mondal, Praful D. Mankar, Goutam Das +2
This article proposes Convolutional Neural Network-based Auto Encoder (CNN-AE) to predict location-dependent rate and coverage probability of a network from its topology. We train…