68 citations · 265 across the 47 of their papers we have counts for
6 papers · 1 filter
Mean-Field Control based Approximation of Multi-Agent Reinforcement Learning in Presence of a Non-decomposable Shared Global State
Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri
Mean Field Control (MFC) is a powerful approximation tool to solve large-scale Multi-Agent Reinforcement Learning (MARL) problems. However, the success of MFC relies on the presump…
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…
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…
On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)
Washim Uddin Mondal, Mridul Agarwal, Vaneet Aggarwal +1
Mean field control (MFC) is an effective way to mitigate the curse of dimensionality of cooperative multi-agent reinforcement learning (MARL) problems. This work considers a collec…
City2City: Translating Place Representations across Cities
Takahiro Yabe, Kota Tsubouchi, Toru Shimizu +2
Large mobility datasets collected from various sources have allowed us to observe, analyze, predict and solve a wide range of important urban challenges. In particular, studies hav…