ML p(r)ior | Distributed Constrained Recursive Nonlinear Least-Squares Estimation: Algorithms and Asymptotics

Distributed Constrained Recursive Nonlinear Least-Squares Estimation: Algorithms and Asymptotics

2016-02-01
This paper focuses on the problem of recursive nonlinear least squares parameter estimation in multi-agent networks, in which the individual agents observe sequentially over time an independent and identically distributed (i.i.d.) time-series consisting of a nonlinear function of the true but unknown parameter corrupted by noise. A distributed recursive estimator of the \emph{consensus} + \emph{innovations} type, namely $\mathcal{CIWNLS}$, is proposed, in which the agents update their parameter estimates at each observation sampling epoch in a collaborative way by simultaneously processing the latest locally sensed information~(\emph{innovations}) and the parameter estimates from other agents~(\emph{consensus}) in the local neighborhood conforming to a pre-specified inter-agent communication topology. Under rather weak conditions on the connectivity of the inter-agent communication and a \emph{global observability} criterion, it is shown that at every network agent, the proposed algorithm leads to consistent parameter estimates. Furthermore, under standard smoothness assumptions on the local observation functions, the distributed estimator is shown to yield order-optimal convergence rates, i.e., as far as the order of pathwise convergence is concerned, the local parameter estimates at each agent are as good as the optimal centralized nonlinear least squares estimator which would require access to all the observations across all the agents at all times. In order to benchmark the performance of the proposed distributed $\mathcal{CIWNLS}$ estimator with that of the centralized nonlinear least squares estimator, the asymptotic normality of the estimate sequence is established and the asymptotic covariance of the distributed estimator is evaluated. Finally, simulation results are presented which illustrate and verify the analytical findings.
PDF

Highlights - Most important sentences from the article

Login to like/save this paper, take notes and configure your recommendations

Related Articles

2018-02-23

We consider the problem of \emph{fully decentralized} multi-agent reinforcement learning (MARL), whe… show more
PDF

Highlights - Most important sentences from the article

2019-02-28

In this paper, we study a distributed parameter estimation problem with an asynchronous communicatio… show more
PDF

Highlights - Most important sentences from the article

2018-07-31
1807.11878 | cs.SY

Consider a set of agents that wish to estimate a vector of parameters of their mutual interest. For … show more
PDF

Highlights - Most important sentences from the article

2019-02-03
1902.00862 | math.OC

In this paper, we study a distributed optimization problem for a class of high-order multi-agent sys… show more
PDF

Highlights - Most important sentences from the article

2019-03-21
1903.09255 | cs.LG

In this paper, we propose a distributed off-policy actor critic method to solve multi-agent reinforc… show more
PDF

Highlights - Most important sentences from the article

2019-03-18

This paper studies the estimation of network weights for a class of systems with binary-valued obser… show more
PDF

Highlights - Most important sentences from the article

2019-03-18

In this paper, we consider a secure distributed filtering problem for linear time-invariant systems … show more
PDF

Highlights - Most important sentences from the article

2018-11-19

This paper addresses the problem of distributed learning of average belief with sequential observati… show more
PDF

Highlights - Most important sentences from the article

2013-10-15

Optimal experiment design for parameter estimation is a research topic that has been in the interest… show more
PDF

Highlights - Most important sentences from the article

2018-10-16
1810.10086 | cs.SY

This work considers resilient, cooperative state estimation in unreliable multi-agent networks. A ne… show more
PDF

Highlights - Most important sentences from the article

2018-09-18

This paper considers the identification of FIR systems, where information about the inputs and outpu… show more
PDF

Highlights - Most important sentences from the article

2018-06-03

Despite the success of single-agent reinforcement learning, multi-agent reinforcement learning (MARL… show more
PDF

Highlights - Most important sentences from the article

2017-06-16
1706.05441 | math.OC

In this paper, we develop a class of decentralized algorithms for solving a convex resource allocati… show more
PDF

Highlights - Most important sentences from the article

2019-03-28
1903.12018 | cs.SY

We consider the problem of optimal decentralized estimation of a linear stochastic process by multip… show more
PDF

Highlights - Most important sentences from the article

2017-11-14

In this paper, we investigate a distributed estimation problem for multi-agent systems with state eq… show more
PDF

Highlights - Most important sentences from the article

2018-07-31
1807.11631 | cs.SY

In this paper, we present a consensus-based framework for decentralized estimation of deterministic … show more
PDF

Highlights - Most important sentences from the article