18 papers
Decentralized Best-Response-Based Learning in Two-Player Zero-Sum Stochastic Games: A Finite-Sample Analysis
Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar +2
We present a finite-sample analysis of decentralized learning in two-player zero-sum matrix games and stochastic games, with a focus on best-response-based learning algorithms. In…
Leveraging Machine-Learned Advice in Strategic Interactions with No-Regret Learners
Tinashe Handina, Tongxin Li, Kishan Panaganti +2
We study how an agent in a two-player repeated game can effectively utilize potentially imperfect advice when interacting with a no-regret learner. We characterize the advice lands…
Small Bottle, Big Pipe: Quantifying and Addressing the Impact of Data Centers on Public Water Systems
Yuelin Han, Pengfei Li, Adam Wierman +1
Water is a critical resource for data centers and an efficient means of cooling. However, meeting the growing water demand of data centers requires substantial peak water withdrawa…
Graphon Mean-Field Subsampling for Cooperative Heterogeneous Multi-Agent Reinforcement Learning
Emile Anand, Richard Hoffmann, Sarah Liaw +1
Coordinating large populations of interacting agents is a central challenge in multi-agent reinforcement learning (MARL), where the size of the joint state-action space scales expo…
Distributionally Robust Cooperative Multi-Agent Reinforcement Learning via Robust Value Factorization
Chengrui Qu, Christopher Yeh, Kishan Panaganti +2
Cooperative multi-agent reinforcement learning (MARL) commonly adopts centralized training with decentralized execution, where value-factorization methods enforce the individual-gl…
Efficient Policy Optimization in Robust Constrained MDPs with Iteration Complexity Guarantees
Sourav Ganguly, Kishan Panaganti, Arnob Ghosh +1
Constrained decision-making is essential for designing safe policies in real-world control systems, yet simulated environments often fail to capture real-world adversities. We cons…