89 citations · 129 across the 22 of their papers we have counts for
6 papers · 1 filter
Reinforcement Learning with an Abrupt Model Change
Wuxia Chen, Taposh Banerjee, Jemin George +1
The problem of reinforcement learning is considered where the environment or the model undergoes a change. An algorithm is proposed that an agent can apply in such a problem to ach…
Asynchronous Distributed Reinforcement Learning for LQR Control via Zeroth-Order Block Coordinate Descent
Gangshan Jing, He Bai, Jemin George +2
Recently introduced distributed zeroth-order optimization (ZOO) algorithms have shown their utility in distributed reinforcement learning (RL). Unfortunately, in the gradient estim…
Learning Distributed Stabilizing Controllers for Multi-Agent Systems
Gangshan Jing, He Bai, Jemin George +2
We address the problem of model-free distributed stabilization of heterogeneous multi-agent systems using reinforcement learning (RL). Two algorithms are developed. The first algor…
Decomposability and Parallel Computation of Multi-Agent LQR
Gangshan Jing, He Bai, Jemin George +1
Individual agents in a multi-agent system (MAS) may have decoupled open-loop dynamics, but a cooperative control objective usually results in coupled closed-loop dynamics thereby m…
Model-Free Optimal Control of Linear Multi-Agent Systems via Decomposition and Hierarchical Approximation
Gangshan Jing, He Bai, Jemin George +1
Designing the optimal linear quadratic regulator (LQR) for a large-scale multi-agent system (MAS) is time-consuming since it involves solving a large-size matrix Riccati equation.…
Hierarchical Control of Multi-Agent Systems using Online Reinforcement Learning
He Bai, Jemin George, Aranya Chakrabortty
We propose a new reinforcement learning based approach to designing hierarchical linear quadratic regulator (LQR) controllers for heterogeneous linear multi-agent systems with unkn…