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04/22/2023
Reinforcement Learning with an Abrupt Model Change
The problem of reinforcement learning is considered where the environmen...
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11/16/2022
Asynchronous Bayesian Learning over a Network
We present a practical asynchronous data fusion model for networked agen...
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02/26/2022
A Scalable Graph-Theoretic Distributed Framework for Cooperative Multi-Agent Reinforcement Learning
The main challenge of large-scale cooperative multi-agent reinforcement ...
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01/10/2022
Distributed Cooperative Multi-Agent Reinforcement Learning with Directed Coordination Graph
Existing distributed cooperative multi-agent reinforcement learning (MAR...
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07/26/2021
Asynchronous Distributed Reinforcement Learning for LQR Control via Zeroth-Order Block Coordinate Descent
Recently introduced distributed zeroth-order optimization (ZOO) algorith...
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10/16/2020
Hierarchical Reinforcement Learning for Optimal Control of Linear Multi-Agent Systems: the Homogeneous Case
Individual agents in a multi-agent system (MAS) may have decoupled open-...
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08/14/2020
Model-Free Optimal Control of Linear Multi-Agent Systems via Decomposition and Hierarchical Approximation
Designing the optimal linear quadratic regulator (LQR) for a large-scale...
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07/14/2020
A Decentralized Approach to Bayesian Learning
Motivated by decentralized approaches to machine learning, we propose a ...
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05/13/2020
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization
In this paper, we consider the problem of communication-efficient decent...
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10/31/2019
SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Stochastic Optimization
In this paper, we propose and analyze SPARQ-SGD, which is an event-trigg...
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09/08/2019
Distributed Deep Learning with Event-Triggered Communication
We develop a Distributed Event-Triggered Stochastic GRAdient Descent (DE...
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09/22/2016