Book ChapterDOI
The Common-Information Approach to Decentralized Stochastic Control
Ashutosh Nayyar,Aditya Mahajan,Demosthenis Teneketzis +2 more
- pp 123-156
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TLDR
This chapter presents the common-information approach to decentralized stochastic control, and describes this approach for a general model and illustrates it by examples from real-time communication, networked control systems, paging and registration in cellular systems, and multi-access broadcast systems.Abstract:
Decentralized stochastic control arises in multi-stage decision-making with multiple decision-makers having different information and a common objective. Examples include cyber-physical systems, communication networks, sensing and surveillance systems, transportation systems, etc. In this chapter, we present the common-information approach to decentralized stochastic control. The key idea behind this approach is to formulate an equivalent centralized stochastic control problem from the point of view of a fictitious coordinator that observes only the information that is commonly available to all decision-makers. The optimal control problem for the fictitious coordinator is shown to be a partially observable Markov decision process (POMDP) which can be solved using techniques from Markov decision theory. We describe this approach for a general model and illustrate it by examples from real-time communication, networked control systems, paging and registration in cellular systems, and multi-access broadcast systems.read more
Citations
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Book
A Concise Introduction to Decentralized POMDPs
TL;DR: This book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs).
Journal ArticleDOI
Optimal Strategies for Communication and Remote Estimation With an Energy Harvesting Sensor
TL;DR: In this paper, the authors considered a distributed estimation problem with an energy harvesting sensor and a remote estimator, where the sensor observes the state of a discrete-time source which may be a finite state Markov chain or a multidimensional linear Gaussian system.
Decentralized wald problem.
TL;DR: In this paper, it is shown that two detectors making independent observations must decide which one of two hypotheses is true and the decisions are coupled through a common cost function, and that the detectors' optimal decisions are characterized by thresholds which are coupled and whose computation requires the solution of two coupled sets of dynamic programming equations.
Journal ArticleDOI
Game Theory and Control
Jason R. Marden,Jeff S. Shamma +1 more
TL;DR: An introduction to game theory is presented, followed by a sampling of results in three specific control theory topics where game theory has played a significant role: zero-sum games, in which the two competing players are a controller and an adversarial environment.
Journal ArticleDOI
On the Existence of Optimal Policies for a Class of Static and Sequential Dynamic Teams
TL;DR: It is shown that a large class of dynamic linear-quadratic-Gaussian teams, including the vector version of the well-known Witsenhausen's counterexample and the Gaussian relay channel problem viewed as a dynamic team, admit team-optimal solutions.
References
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