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Inference with Minimal Communication: a Decision-Theoretic Variational Approach
2005
Neural Information Processing Systems
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We present a variational formulation, viewing the processing rules local to all nodes as degrees-of-freedom, that minimizes the loss in expected (MAP or MPM) performance subject to such online communication ...
We are grateful to Professor John Tsitsiklis for taking time to discuss the correctness of Proposition 1. ...
Decentralized detection has roots in team decision theory [7] , a subset of game theory, in which the relaxation is named person-by-person (pbp) optimality. ...
dblp:conf/nips/KreidlW05
fatcat:vvzocjkmfzb4fdpruwljelvsqe
Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Processes
[article]
2017
arXiv
pre-print
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Since macro-actions last for stochastic durations, multiple agents executing decentralized policies in cooperative environments must act asynchronously. ...
The incorporation of macro-actions (temporally extended actions) into multi-agent decision problems has the potential to address the curse of dimensionality associated with such decision problems. ...
The authors would also like to thank the anonymous reviewers for their helpful comments. ...
arXiv:1709.06656v1
fatcat:gfd7c37xnrhidjnlno44q7rtta
An efficient Monte Carlo approach for optimizing decentralized estimation networks constrained by undirected topologies
2009
2009 IEEE/SP 15th Workshop on Statistical Signal Processing
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Index Terms-Decentralized estimation, communication constrained inference, random-field estimation, message passing algorithms. 1. ...
We adopt this framework for decentralized estimation (DE) and present the corresponding iterative scheme. ...
Adopting a recent scheme for detection networks which proposes a solution utilizing team decision theory we have extended the set of constraints considered by the conventional approaches for the decentralized ...
doi:10.1109/ssp.2009.5278534
fatcat:bvjoxzvln5c5jlg63c6evxk5hy
Policy Iteration for Decentralized Control of Markov Decision Processes
2009
The Journal of Artificial Intelligence Research
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As a formal framework for such problems, we use the decentralized partially observable Markov decision process (DEC-POMDP). ...
Though much work has been done on optimal dynamic programming algorithms for the single-agent version of the problem, optimal algorithms for the multiagent case have been elusive. ...
Acknowledgments We thank Martin Allen, Marek Petrik and Siddharth Srivastava for helpful discussions of this work. Marek and Siddharth, in particular, helped formalize and prove Theorem 1. ...
doi:10.1613/jair.2667
fatcat:expklgkvdzbyvffwa32xfteeca
Distributed learning in wireless sensor networks
2006
IEEE Signal Processing Magazine
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Applications such as these pave the way for a nonparametric study of distributed detection and estimation. ...
In this paper, we review recent work of the authors in which some elementary models for distributed learning are considered. ...
In general, extending the above results to realistic sampling processes is of practical importance. ...
doi:10.1109/msp.2006.1657817
fatcat:xdabigmwbbgidjpte427qs6ptm
Markov Decision Processes With Applications in Wireless Sensor Networks: A Survey
2015
IEEE Communications Surveys and Tutorials
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This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. ...
Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs. ...
Extensions of Markov decision models. · MDP
: Markov decision process
· POMDP
: Partially observable Markov decision process
· MMDP
: Multi-agent Markov decision process
· DEC-POMDP : Decentralized ...
doi:10.1109/comst.2015.2420686
fatcat:422xkiciufedpljgcmfrwownau
Designing autonomous layered video coders
2009
Signal processing. Image communication
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In this paper, we propose a framework for autonomous decision making in layered video coders, which decouples the decision making processes at the various layers using a novel layered Markov decision process ...
We illustrate how this framework can be applied to decompose the decision processes for several typical layered video coders with different dependency structures and we observe that the performance of ...
Acknowledgments The authors would like to thank Fangwen Fu for his valuable technical help throughout the writing of this paper. ...
doi:10.1016/j.image.2009.02.009
fatcat:kmu6zr3tsjgi3ajmgobdfes3ze
Design of false data injection attack on distributed process estimation
[article]
2021
arXiv
pre-print
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To this end, a constrained optimization problem is formulated to find the optimal parameter values of a certain class of linear attacks. ...
The problem turns out to be convex for some special cases. Desired convergence of the proposed algorithms are proved by exploiting the convexity and properties of stochastic approximation algorithms. ...
average-cost Markov decision process (MDP; see [32]) to
X
E(||θ (k) (t)||2 |Ft−1 ) = ||(A − Gk Tk Hk ...
arXiv:2101.05567v1
fatcat:y2gdcq765zftxo2o735vxxjiju
Design of False Data Injection Attack on Distributed Process Estimation
2022
IEEE Transactions on Information Forensics and Security
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See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. ...
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. ...
Updating λ(t) iteratively: OLAADE-KKT Note that, solving (CP) will require us to solve a constrained average-cost Markov decision process (MDP; see [43] ) to find an optimal policy, since the decision ...
doi:10.1109/tifs.2022.3146078
fatcat:bhbr3zda4valndqelbleo5fbeu
Monte Carlo Optimization of Decentralized Estimation Networks Over Directed Acyclic Graphs Under Communication Constraints
2011
IEEE Transactions on Signal Processing
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This perspective captures a broad range of possibilities for processing under network constraints and enables a rigorous design problem in the form of constrained optimization. ...
We develop an approximation framework using Monte Carlo methods and obtain particle representations and approximate computational schemes for both the in-network processing strategies and their optimization ...
Index Terms Decentralized estimation, communication constrained inference, random fields, message passing algorithms, graphical models, Monte Carlo methods, wireless sensor networks, in-network processing ...
doi:10.1109/tsp.2011.2163629
fatcat:z5pamuva5nbqtmtuts5v2l6xmu
A Survey on Time-Sensitive Resource Allocation in the Cloud Continuum
[article]
2020
arXiv
pre-print
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The cloud and edge platform is very crucial to these applications due to their inherent compute-intensive and resource-constrained nature. ...
Artificial Intelligence (AI) and Internet of Things (IoT) applications are rapidly growing in today's world where they are continuously connected to the internet and process, store and exchange information ...
ACKNOWLEDGMENTS This work was financially supported in part by the Singapore National Research Foundation under its Campus for Research Excellence And Technological Enterprise (CREATE) programme. ...
arXiv:2004.14559v1
fatcat:ohshzqpndff65dzpqtpn2rx2gu
2014 Index IEEE Transactions on Automatic Control Vol. 59
2014
IEEE Transactions on Automatic Control
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., +, TAC Oct. 2014 2796-2800 Efficient Algorithms for Budget-Constrained Markov Decision Processes. ...
Necoara, I., +, TAC May 2014 1232-1243
Risk-Constrained Markov Decision Processes. ...
doi:10.1109/tac.2014.2382720
fatcat:jah5kqkafvejrd7xpvyikmi53e
Midpoint routing algorithms for Delaunay triangulations
2010
2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS)
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Abstract Extending the standard Java virtual machine (JVM) for cluster-awareness is a transparent approach to scaling out multithreaded Java applications. ...
large number of nodes for processing massive amounts of data. ...
Abstract In this paper we study algorithms for performing the LU and QR factorizations of dense matrices. ...
doi:10.1109/ipdps.2010.5470471
dblp:conf/ipps/SiZ10
fatcat:yuchdc4zp5borm5vs7j4rqgmzy
A Combined Multiple Model Adaptive Control Scheme and Its Application to Nonlinear Systems With Nonlinear Parameterization
2012
IEEE Transactions on Automatic Control
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Author's reply to comments on "Decentralized stabilization of intercon- ...
., +, TAC July 2012 1736-1751
Decision theory
Mean Field for Markov Decision Processes: From Discrete to Continuous
Optimization. ...
., +, TAC Jan. 2012 249-254
Networked Markov Decision Processes With Delays. ...
doi:10.1109/tac.2011.2176162
fatcat:2airdooti5fi7kmuozmodywcga
2013 Index IEEE Transactions on Automatic Control Vol. 58
2013
IEEE Transactions on Automatic Control
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-Y., +, TAC June 2013 1540-1545 Markov processes A Matrosov Theorem for Adversarial Markov Decision Processes. Teel, A. ...
., +, TAC May 2013 1317-1322 Decision theory Constrained Partially Observed Markov Decision Processes With Probabilistic Criteria for Adaptive Sequential Detection. Chen, R. ...
Signal processing Bode ...
doi:10.1109/tac.2013.2295962
fatcat:3zpqog4r4nhoxgo4vodx4sj3l4
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