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Related papers: Decentralized Stochastic Control with Partial Hist…

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In decentralized stochastic control, standard approaches for sequential decision-making, e.g. dynamic programming, quickly become intractable due to the need to maintain a complex information state. Computational challenges are further…

Machine Learning · Computer Science 2019-08-08 Kaiqing Zhang , Erik Miehling , Tamer Başar

Decentralized stochastic control refers to the multi-stage optimization of a dynamical system by multiple controllers that have access to different information. Decentralization of information gives rise to new conceptual challenges that…

Optimization and Control · Mathematics 2013-10-18 Aditya Mahajan , Mehnaz Mannan

We describe a probabilistic framework for synthesizing control policies for general multi-robot systems, given environment and sensor models and a cost function. Decentralized, partially observable Markov decision processes (Dec-POMDPs) are…

We introduce an expressive framework and algorithms for the semi-decentralized control of cooperative agents in environments with communication uncertainty. Whereas semi-Markov control admits a distribution over time for agent actions,…

Artificial Intelligence · Computer Science 2026-03-13 Mahdi Al-Husseini , Mykel J. Kochenderfer , Kyle H. Wray

This paper develops a dynamic programming (DP) approach for decentralized stochastic optimal control problems with delayed sharing information patterns, which exhibits the fundamental Properties of classical DP of centralized partially…

Systems and Control · Electrical Eng. & Systems 2026-04-28 Charalambos D. Charalambous , Umarbek Guvercin , Seddik Djouadi

Multi-agent planning in stochastic environments can be framed formally as a decentralized Markov decision problem. Many real-life distributed problems that arise in manufacturing, multi-robot coordination and information gathering scenarios…

Artificial Intelligence · Computer Science 2011-11-02 Claudia V. Goldman , Shlomo Zilberstein

We present existence and discrete-time approximation results on optimal control policies for continuous-time stochastic control problems under a variety of information structures. These include fully observed models, partially observed…

Optimization and Control · Mathematics 2025-03-13 Somnath Pradhan , Serdar Yüksel

Decentralized stochastic control problems involving general state/measurement/action spaces are intrinsically difficult to study because of the inapplicability of standard tools from centralized (single-agent) stochastic control. In this…

Optimization and Control · Mathematics 2025-11-10 Omar Mrani-Zentar , Serdar Yüksel

Coordination of distributed agents is required for problems arising in many areas, including multi-robot systems, networking and e-commerce. As a formal framework for such problems, we use the decentralized partially observable Markov…

Artificial Intelligence · Computer Science 2014-01-16 Daniel S. Bernstein , Christopher Amato , Eric A. Hansen , Shlomo Zilberstein

An information based method for solving stochastic control problems with partial observation has been proposed. First, the information-theoretic lower bounds of the cost function has been analysed. It has been shown, under rather weak…

Optimization and Control · Mathematics 2019-11-21 Piotr Bania

Distributed model predictive control (MPC) has been proven a successful method in regulating the operation of large-scale networks of constrained dynamical systems. This paper is concerned with cooperative distributed MPC in which the…

Optimization and Control · Mathematics 2021-06-29 Georgios Darivianakis , Angelos Georghiou , John Lygeros

The $n$-step delayed sharing information structure is investigated. This information structure comprises of $K$ controllers that share their information with a delay of $n$ time steps. This information structure is a link between the…

Other Computer Science · Computer Science 2011-12-30 Ashutosh Nayyar , Aditya Mahajan , Demosthenis Teneketzis

This paper considers the optimal decentralized control for networked control systems (NCSs) with asymmetric partial information sharing between two controllers. In this NCSs model, the controller 2 (C2) shares its observations and part of…

Optimization and Control · Mathematics 2019-11-07 Xiao Liang , Qingyuan Qi , Huanshui Zhang , Lihua Xie

A key issue in the control of distributed discrete systems modeled as Markov decisions processes, is that often the state of the system is not directly observable at any single location in the system. The participants in the control scheme…

Information Theory · Computer Science 2017-05-01 Jie Ren , Solmaz Torabi , John MacLaren Walsh

In this paper, we investigate a decentralized stochastic control problem with two agents, where a part of the memory of the second agent is also available to the first agent at each instance of time. We derive a structural form for optimal…

Optimization and Control · Mathematics 2022-06-14 Aditya Dave , Nishanth Venkatesh , Andreas A. Malikopoulos

Decentralized stochastic control problems are difficult to study due to information structure dependent subtleties, which prevent many classical methods in stochastic control from being applicable. In this paper we consider such problems…

Optimization and Control · Mathematics 2026-05-04 Omar Mrani-Zentar , Serdar Yuksel

Subsystems that are coupled due to dynamics and costs arise naturally in various communication applications. In many such applications the control actions are shared between different control stations giving rise to a \emph{control sharing}…

Systems and Control · Computer Science 2012-08-09 Aditya Mahajan

In this paper, we investigate a decentralized control problem with nested subsystems, which is a general model for one-directional communication amongst many subsystems. The noises in our dynamics are modelled as uncertain variables which…

Optimization and Control · Mathematics 2022-06-14 Aditya Dave , Nishanth Venkatesh , Andreas A. Malikopoulos

We consider the decentralized control of a discrete-time, linear system subject to exogenous disturbances and polyhedral constraints on the state and input trajectories. The underlying system is composed of a finite collection of…

Optimization and Control · Mathematics 2020-04-08 Weixuan Lin , Eilyan Bitar

Planning for distributed agents with partial state information is considered from a decision- theoretic perspective. We describe generalizations of both the MDP and POMDP models that allow for decentralized control. For even a small number…

Artificial Intelligence · Computer Science 2013-01-18 Daniel S Bernstein , Shlomo Zilberstein , Neil Immerman
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