238 citations · 810 across the 47 of their papers we have counts for
53 papers
Model-free Learning for Risk-constrained Linear Quadratic Regulator with Structured Feedback in Networked Systems
Kyung-bin Kwon, Lintao Ye, Vijay Gupta +1
We develop a model-free learning algorithm for the infinite-horizon linear quadratic regulator (LQR) problem. Specifically, (risk) constraints and structured feedback are considere…
Resilient Consensus-based Multi-agent Reinforcement Learning with Function Approximation
Martin Figura, Yixuan Lin, Ji Liu +1
Adversarial attacks during training can strongly influence the performance of multi-agent reinforcement learning algorithms. It is, thus, highly desirable to augment existing algor…
Finite-Time Error Bounds for Distributed Linear Stochastic Approximation
Yixuan Lin, Vijay Gupta, Ji Liu
This paper considers a novel multi-agent linear stochastic approximation algorithm driven by Markovian noise and general consensus-type interaction, in which each agent evolves acc…
On the Sample Complexity of Decentralized Linear Quadratic Regulator with Partially Nested Information Structure
Lintao Ye, Hao Zhu, Vijay Gupta
We study the problem of control policy design for decentralized state-feedback linear quadratic control with a partially nested information structure, when the system model is unkn…
Data-Driven Contract Design for Multi-Agent Systems with Collusion Detection
Nayara Aguiar, Parv Venkitasubramaniam, Vijay Gupta
In applications such as participatory sensing and crowd sensing, self-interested agents exert costly effort towards achieving an objective for the system operator. We study such a…
Adversarial attacks in consensus-based multi-agent reinforcement learning
Martin Figura, Krishna Chaitanya Kosaraju, Vijay Gupta
Recently, many cooperative distributed multi-agent reinforcement learning (MARL) algorithms have been proposed in the literature. In this work, we study the effect of adversarial a…