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06/09/2023
Approximate information state based convergence analysis of recurrent Q-learning
In spite of the large literature on reinforcement learning (RL) algorith...
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02/06/2023
Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning
Decentralized cooperative multi-agent deep reinforcement learning (MARL)...
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11/06/2022
On learning history based policies for controlling Markov decision processes
Reinforcementlearning(RL)folkloresuggeststhathistory-basedfunctionapprox...
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02/07/2022
On learning Whittle index policy for restless bandits with scalable regret
Reinforcement learning is an attractive approach to learn good resource ...
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12/20/2021
Consistency and Rate of Convergence of Switched Least Squares System Identification for Autonomous Switched Linear Systems
In this paper, we investigate the problem of system identification for a...
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11/11/2021
Scalable Operator Allocation for Multi-Robot Assistance: A Restless Bandit Approach
In this paper, we consider the problem of allocating human operators in ...
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10/05/2021
Robustness and sample complexity of model-based MARL for general-sum Markov games
Multi-agent reinfocement learning (MARL) is often modeled using the fram...
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08/19/2021
A relaxed technical assumption for posterior sampling-based reinforcement learning for control of unknown linear systems
We revisit the Thompson sampling algorithm to control an unknown linear ...
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08/18/2021
Scalable regret for learning to control network-coupled subsystems with unknown dynamics
We consider the problem of controlling an unknown linear quadratic Gauss...
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06/29/2021
Structure-aware reinforcement learning for node-overload protection in mobile edge computing
Mobile Edge Computing (MEC) refers to the concept of placing computation...
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11/09/2020
Thompson sampling for linear quadratic mean-field teams
We consider optimal control of an unknown multi-agent linear quadratic (...
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10/17/2020
Approximate information state for approximate planning and reinforcement learning in partially observed systems
We propose a theoretical framework for approximate planning and learning...
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04/24/2020
Decentralized linear quadratic systems with major and minor agents and non-Gaussian noise
We consider a decentralized linear quadratic system with a major agent a...
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10/08/2019
Counterexamples on the monotonicity of delay optimal strategies for energy harvesting transmitters
We consider cross-layer design of delay optimal transmission strategies ...
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07/25/2018
Remote estimation over a packet-drop channel with Markovian state
We investigate a remote estimation problem in which a transmitter observ...
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04/03/2018
Renewal Monte Carlo: Renewal theory based reinforcement learning
In this paper, we present an online reinforcement learning algorithm, ca...
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05/08/2012
