collaborators

13 papers

cs.MA2026

Resilient Decentralized Ergodic Coverage for Scalable Multi-Robot Systems in Unknown Time-Varying Environments

Maria G. Mendoza, Victoria Marie Tuck, Chinmay Maheshwari +1

Maintaining situational awareness in high-stakes multi-robot applications requires balancing exploration of unobserved regions with sustained monitoring of changing Regions of Inte…

math.OC2026

EXOTIC: An Exact, Optimistic, Tree-Based Algorithm for Min-Max Optimization

Chinmay Maheshwari, Chinmay Pimpalkhare, Debasish Chatterjee

Min-max optimization arises in many domains such as game theory, adversarial machine learning, etc. For these problems, gradient-based methods are well understood and enjoy strong…

cs.MA2026

Nash Approximation Gap in Truncated Infinite-horizon Partially Observable Markov Games

Lan Sang, Chinmay Maheshwari

Partially Observable Markov Games (POMGs) provide a general framework for modeling multi-agent sequential decision-making under asymmetric information. A common approach is to refo…

cs.LG2026

NePPO: Near-Potential Policy Optimization for General-Sum Multi-Agent Reinforcement Learning

Addison Kalanther, Sanika Bharvirkar, Shankar Sastry +1

Multi-agent reinforcement learning (MARL) is increasingly used to design learning-enabled agents that interact in shared environments. However, training MARL algorithms in general-…

cs.GT2026

Game-to-Real Gap: Quantifying the Effect of Model Misspecification in Network Games

Bryce L. Ferguson, Chinmay Maheshwari, Manxi Wu +1

Game-theoretic models and solution concepts provide rigorous tools for predicting collective behavior in multi-agent systems. In practice, however, different agents may rely on dif…

cs.MA2025

Evader-Agnostic Team-Based Pursuit Strategies in Partially-Observable Environments

Addison Kalanther, Daniel Bostwick, Chinmay Maheshwari +1

We consider a scenario where a team of two unmanned aerial vehicles (UAVs) pursue an evader UAV within an urban environment. Each agent has a limited view of their environment wher…