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Static reduction of information structures (ISs) is a method that is commonly adopted in stochastic control, team theory, and game theory. One approach entails change of measure arguments, which has been crucial for stochastic analysis and…

Optimization and Control · Mathematics 2023-07-13 Sina Sanjari , Tamer Başar , Serdar Yüksel

In this paper, we establish the existence of team-optimal policies for static teams and a class of sequential dynamic teams. We first consider the static team problems and show the existence of optimal policies under certain regularity…

Systems and Control · Computer Science 2017-11-03 Naci Saldı

We study stochastic static teams with countably infinite number of decision makers, with the goal of obtaining (globally) optimal policies under a decentralized information structure. We present sufficient conditions to connect the concepts…

Optimization and Control · Mathematics 2020-05-14 Sina Sanjari , Serdar Yüksel

Decentralized optimization of distributed stochastic differential systems has been an active area of research for over half a century. Its formulation utilizing static team and person-by-person optimality criteria is well investigated.…

Optimization and Control · Mathematics 2013-02-15 Charalambos D. Charalambous , Nasir U. Ahmed

In this paper, we identify sufficient conditions under which static teams and a class of sequential dynamic teams admit team-optimal solutions. We first investigate the existence of optimal solutions in static teams where the observations…

Systems and Control · Computer Science 2014-04-08 Abhishek Gupta , Serdar Yuksel , Tamer Basar , Cedric Langbort

In this paper, we demonstrate the existence of team-optimal strategies for static teams under observation-sharing information structures. Assuming that agents can access shared observations, we begin by converting the team problem into an…

Systems and Control · Electrical Eng. & Systems 2023-09-15 Naci Saldi

We study stochastic team (known also as decentralized stochastic control or identical interest stochastic dynamic game) problems with large or countably infinite number of decision makers, and characterize existence and structural…

Optimization and Control · Mathematics 2021-07-08 Sina Sanjari , Naci Saldi , Serdar Yüksel

In this paper, we present two methods which generalize static team theory to dynamic team theory, in the context of continuous-time stochastic nonlinear differential decentralized decision systems, with relaxed strategies, which are…

Optimization and Control · Mathematics 2013-10-11 Charalambos D. Charalambous , Nasir U. Ahmed

This paper is concerned with the properties of the sets of strategic measures induced by admissible team policies in decentralized stochastic control and the convexity properties in dynamic team problems. To facilitate a convex analytical…

Optimization and Control · Mathematics 2016-11-01 Serdar Yüksel , Naci Saldi

This paper studies convex stochastic dynamic team problems with finite and infinite time horizons under decentralized information structures. First, we introduce two notions called exchangeable teams and symmetric information structures. We…

Optimization and Control · Mathematics 2020-11-25 Sina Sanjari , Serdar Yüksel

This paper develops a unified methodology for probabilistic analysis and optimal control design for jump diffusion processes defined by polynomials. For such systems, the evolution of the moments of the state can be described via a system…

Optimization and Control · Mathematics 2017-02-03 Andrew Lamperski , Khem Raj Ghusinga , Abhyudai Singh

Stochastic optimization problems often involve data distributions that change in reaction to the decision variables. This is the case for example when members of the population respond to a deployed classifier by manipulating their features…

Optimization and Control · Mathematics 2020-12-15 Dmitriy Drusvyatskiy , Lin Xiao

In this second part of our two-part paper, we invoke the stochastic maximum principle, conditional Hamiltonian and the coupled backward-forward stochastic differential equations of the first part [1] to derive team optimal decentralized…

Optimization and Control · Mathematics 2013-02-15 Charalambos D. Charalambous , Nasir U. Ahmed

For sequential stochastic control problems with standard Borel measurement and control action spaces, we introduce a general (universally applicable) dynamic programming formulation, establish its well-posedness, and provide new existence…

Optimization and Control · Mathematics 2020-07-02 Serdar Yüksel

In this paper, we consider finite model approximations of a large class of static and dynamic team problems where these models are constructed through uniform quantization of the observation and action spaces of the agents. The strategies…

Optimization and Control · Mathematics 2016-01-05 Naci Saldi , Serdar Yüksel , Tamás Linder

Stochastic dynamic teams and games are rich models for decentralized systems and challenging testing grounds for multi-agent learning. Previous work that guaranteed team optimality assumed stateless dynamics, or an explicit coordination…

Optimization and Control · Mathematics 2024-03-28 Bora Yongacoglu , Gürdal Arslan , Serdar Yüksel

Variational inequalities are a formalism that includes games, minimization, saddle point, and equilibrium problems as special cases. Methods for variational inequalities are therefore universal approaches for many applied tasks, including…

Algorithms of control of differential equations solutions are under investigation in the article. Idealized and real modifications of the algorithms are distinguished. An equation, which can be the base equation for investigation of the…

Numerical Analysis · Computer Science 2016-01-05 Yu. V. Troshchiev

This paper considers two problems -- a dynamic team problem and a decentralized control problem. The problems we consider do not belong to the known classes of "simpler" dynamic team/decentralized control problems such as partially nested…

Systems and Control · Computer Science 2016-11-14 Seyed Mohammad Asghari , Ashutosh Nayyar

Change of measures has been an effective method in stochastic control and analysis; in continuous-time control this follows Girsanov's theorem applied to both fully observed and partially observed models, in decentralized stochastic control…

Optimization and Control · Mathematics 2022-01-20 Ian Hogeboom-Burr , Serdar Yüksel
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