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We introduce a contractive abstract dynamic programming framework and related policy iteration algorithms, specifically designed for sequential zero-sum games and minimax problems with a general structure. Aside from greater generality, the…

Computer Science and Game Theory · Computer Science 2021-10-22 Dimitri Bertsekas

A general model for zero-sum stochastic games with asymmetric information is considered. In this model, each player's information at each time can be divided into a common information part and a private information part. Under certain…

Systems and Control · Electrical Eng. & Systems 2019-12-25 Dhruva Kartik , Ashutosh Nayyar

In this paper, we study a stochastic recursive optimal control problem in which the value functional is defined by the solution of a backward stochastic differential equation (BSDE) under $\tilde{G}$-expectation. Under standard assumptions,…

Optimization and Control · Mathematics 2021-06-08 Mingshang Hu , Shaolin Ji , Xiaojuan Li

We develop an approach for two player constraint zero-sum and nonzero-sum stochastic differential games, which are modeled by Markov regime-switching jump-diffusion processes. We provide the relations between a usual stochastic optimal…

Optimization and Control · Mathematics 2023-01-31 Emel Savku

We generalize the results of Fleming and Souganidis (1989) on zero sum stochastic differential games to the case when the controls are unbounded. We do this by proving a dynamic programming principle using a covering argument instead of…

Optimization and Control · Mathematics 2012-01-17 Erhan Bayraktar , Song Yao

Differential Dynamic Programming (DDP) is one of the indirect methods for solving an optimal control problem. Several extensions to DDP have been proposed to add stagewise state and control constraints, which can mainly be classified as…

Optimization and Control · Mathematics 2024-09-19 Siddharth Prabhu , Srinivas Rangarajan , Mayuresh Kothare

Pontryagin type maximum principle and Bellman's dynamic programming principle serve as two of the most important tools in solving optimal control problems. There is a huge literature on the study of relationship between them. The main…

Optimization and Control · Mathematics 2021-12-30 Liangying Chen , Qi Lü

Markov decision processes (MDPs) are used to model a wide variety of applications ranging from game playing over robotics to finance. Their optimal policy typically maximizes the expected sum of rewards given at each step of the decision…

Machine Learning · Computer Science 2025-05-26 Maximilian Nägele , Jan Olle , Thomas Fösel , Remmy Zen , Florian Marquardt

In this work, we study discrete-time Markov decision processes (MDPs) under constraints with Borel state and action spaces and where all the performance functions have the same form of the expected total reward (ETR) criterion over the…

Probability · Mathematics 2019-05-10 F. Dufour , Alexandre Genadot

We consider zero-sum stochastic games for continuous time Markov decision processes with risk-sensitive average cost criterion. Here the transition and cost rates may be unbounded. We prove the existence of the value of the game and a…

Optimization and Control · Mathematics 2021-09-21 Mrinal K. Ghosh , Subrata Golui , Chandan Pal , Somnath Pradhan

This paper studies the optimal control problem for discrete-time nonlinear systems and an approximate dynamic programming-based Model Predictive Control (MPC) scheme is proposed for minimizing a quadratic performance measure. In the…

Systems and Control · Electrical Eng. & Systems 2023-12-12 Keerthi Chacko , Midhun T. Augustine , S. Janardhanan , Deepak U. Patil , I. N. Kar

We consider an autonomous navigation problem, whereby a traveler aims at traversing an environment in which an adversary tries to set an ambush. A two players zero sum game is introduced. Players' strategies are computed as random path…

Robotics · Computer Science 2016-12-08 Emmanuel Boidot , Aude Marzuoli , Eric Feron

We study a two-player discounted zero-sum stochastic game model for dynamic operational planning in military campaigns. At each stage, the players manage multiple commanders who order military actions on objectives that have an open line of…

Computer Science and Game Theory · Computer Science 2024-03-04 Joseph E. McCarthy , Mathieu Dahan , Chelsea C. White

In the present work, we consider 2-person zero-sum stochastic differential games with a nonlinear pay-off functional which is defined through a backward stochastic differential equation. Our main objective is to study for such a game the…

Probability · Mathematics 2014-07-29 Rainer Buckdahn , Juan Li , Marc Quincampoix

Differential Dynamic Programming (DDP) has become a well established method for unconstrained trajectory optimization. Despite its several applications in robotics and controls however, a widely successful constrained version of the…

Optimization and Control · Mathematics 2020-05-05 Yuichiro Aoyama , George Boutselis , Akash Patel , Evangelos A. Theodorou

We establish existence of nearly-optimal controls, conditions for existence of an optimal control and a saddle-point for respectively a control problem and zero-sum differential game associated with payoff functionals of mean-field type,…

Probability · Mathematics 2017-07-25 Boualem Djehiche , Said Hamadène

Determinantal Point Process (DPPs) are statistical models for repulsive point patterns. Both sampling and inference are tractable for DPPs, a rare feature among models with negative dependence that explains their popularity in machine…

Machine Learning · Computer Science 2021-11-30 Michaël Fanuel , Rémi Bardenet

Certain but important classes of strategic-form games, including zero-sum and identical-interest games, have the fictitious-play-property (FPP), i.e., beliefs formed in fictitious play dynamics always converge to a Nash equilibrium (NE) in…

Computer Science and Game Theory · Computer Science 2022-05-24 Muhammed O. Sayin , Kaiqing Zhang , Asuman Ozdaglar

In this paper, motivated by a problem in stochastic impulse control theory, we aim to study solutions to a free boundary problem of obstacle-type. We obtain sharp estimates for the solution using nonlinear tools which are independent of the…

Analysis of PDEs · Mathematics 2017-02-02 Rohit Jain

Dynamical compensation (DC) provides robustness to parameter fluctuations. As an example, DC enable control of the functional mass of endocrine or neuronal tissue essential for controlling blood glucose by insulin through a nonlinear…

Systems and Control · Electrical Eng. & Systems 2024-06-04 Akram Ashyani , Yu-Heng Wu , Huan-Wei Hsu , Torbjörn E. M. Nordling
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