activity
20182026
most citedIndependent and Decentralized Learning in Markov Potential Games

6 citations · 29 across the 16 of their papers we have counts for

collaborators

18 papers

cs.AI2026

Budget-Efficient Automatic Algorithm Design via Code Graph

Maxime Bouscary, Manxi Wu, Saurabh Amin

Large language models (LLMs) have emerged as powerful tools for automatic algorithm design (AAD). However, existing pipelines remain inefficient. They operate at the granularity of…

cs.GT2023

Information Design for Spatial Resource Allocation

Ozan Candogan, Manxi Wu

In this paper, we study platforms where resources and jobs are spatially distributed, and resources have the flexibility to strategically move to different locations for better pay…

cs.GT2023★ 1 cited

Market Design for Capacity Sharing in Networks

Saurabh Amin, Patrick Jaillet, Haripriya Pulyassary +1

We study a market mechanism that sets edge prices to incentivize strategic agents to efficiently share limited network capacity. In this market, agents form coalitions, with each c…

cs.GT2023★ 2 cited

Markov -Potential Games

Xin Guo, Xinyu Li, Chinmay Maheshwari +2

We propose a new framework of Markov -potential games to study Markov games. We show that any Markov game with finite-state and finite-action is a Markov -potential game, and…

cs.MA2023

Capacity Allocation and Pricing of High Occupancy Toll Lane Systems with Heterogeneous Travelers

Haripriya Pulyassary, Ruifan Yang, Zhanhao Zhang +1

In this article, we study the optimal design of High Occupancy Toll (HOT) lanes. In our setup, the traffic authority determines the road capacity allocation between HOT lanes and o…

cs.MA2022

Convergence and Stability of Coupled Belief--Strategy Learning Dynamics in Continuous Games

Manxi Wu, Saurabh Amin, Asuman Ozdaglar

We propose a learning dynamics to model how strategic agents repeatedly play a continuous game while relying on an information platform to learn an unknown payoff-relevant paramete…