Showing cs.MAShow all
3 papers · 1 filter
cs.MA2021
Deep Structured Teams in Arbitrary-Size Linear Networks: Decentralized Estimation, Optimal Control and Separation Principle
Jalal Arabneydi, Amir G. Aghdam
In this article, we introduce decentralized Kalman filters for linear quadratic deep structured teams. The agents in deep structured teams are coupled in dynamics, costs and measur…
cs.MA2020
Reinforcement Learning in Linear Quadratic Deep Structured Teams: Global Convergence of Policy Gradient Methods
Vida Fathi, Jalal Arabneydi, Amir G. Aghdam
In this paper, we study the global convergence of model-based and model-free policy gradient descent and natural policy gradient descent algorithms for linear quadratic deep struct…
cs.MA2020
Reinforcement Learning in Deep Structured Teams: Initial Results with Finite and Infinite Valued Features
Jalal Arabneydi, Masoud Roudneshin, Amir G. Aghdam
In this paper, we consider Markov chain and linear quadratic models for deep structured teams with discounted and time-average cost functions under two non-classical information st…