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A new method for stochastic control based on neural networks and using randomisation of discrete random variables is proposed and applied to optimal stopping time problems. The method models directly the policy and does not need the…

Computational Finance · Quantitative Finance 2021-01-11 Thomas Deschatre , Joseph Mikael

In this article, we discuss two algorithms tailored to discrete-time deterministic finite-horizon nonlinear optimal control problems or so-called deterministic trajectory optimization problems. Both algorithms can be derived from an…

Optimization and Control · Mathematics 2024-12-10 Mohammad Mahmoudi Filabadi , Tom Lefebvre , Guillaume Crevecoeur

In this paper, we investigate dynamic optimization problems featuring both stochastic control and optimal stopping in a finite time horizon. The paper aims to develop new methodologies, which are significantly different from those of mixed…

Portfolio Management · Quantitative Finance 2014-06-27 Xiongfei Jian , Xun Li , Fahuai Yi

In this work, we consider the problem of autonomous racing with multiple agents where agents must interact closely and influence each other to compete. We model interactions among agents through a game-theoretical framework and propose an…

Systems and Control · Electrical Eng. & Systems 2023-05-02 Yixuan Jia , Maulik Bhatt , Negar Mehr

Dual control explicitly addresses the problem of trading off active exploration and exploitation in the optimal control of partially unknown systems. While the problem can be cast in the framework of stochastic dynamic programming, exact…

Systems and Control · Electrical Eng. & Systems 2019-11-12 Elena Arcari , Lukas Hewing , Melanie N. Zeilinger

This paper studies a continuous-time market {under stochastic environment} where an agent, having specified an investment horizon and a target terminal mean return, seeks to minimize the variance of the return with multiple stocks and a…

Portfolio Management · Quantitative Finance 2013-02-28 Wan-Kai Pang , Yuan-Hua Ni , Xun Li , Ka-Fai Cedric Yiu

A very simple example of an algorithmic problem solvable by dynamic programming is to maximize, over sets A in {1,2,...,n}, the objective function |A| - \sum_i \xi_i 1(i \in A,i+1 \in A) for given \xi_i > 0. This problem, with random…

Probability · Mathematics 2007-10-04 David J. Aldous , Charles Bordenave , Marc Lelarge

This paper considers the hidden-action model of the principal-agent problem, in which a principal incentivizes an agent to work on a project using a contract. We investigate whether contracts with bounded payments are learnable and…

Computer Science and Game Theory · Computer Science 2024-02-23 Yurong Chen , Zhaohua Chen , Xiaotie Deng , Zhiyi Huang

A dynamical programming approach is used to deal with the problem of controlling the directed abelian Dhar-Ramaswamy model on two-dimensional square lattice. Two strategies are considered to obtain explicit results to this task. First, the…

Computational Physics · Physics 2015-06-16 Daniel O. Cajueiro , Roberto F. S. Andrade

We study the design of optimal allocation mechanisms in an environment where agents and goods arrive stochastically. Agents have private types that determine the principal payoff. Either agents or goods can be held in a queue at a flow cost…

Theoretical Economics · Economics 2026-02-05 Zihao Li , Xuandong Chen

In this paper, we take up the analysis of a principal/agent model with moral hazard introduced in [17], with optimal contracting between competitive investors and an impatient bank monitoring a pool of long-term loans subject to Markovian…

Probability · Mathematics 2015-04-07 Henri Pagès , Dylan Possamaï

We provide an overview on how to use the measurable selection techniques to derive the dynamic programming principle for a general stochastic optimal control/stopping problem. By considering its martingale problem formulation on the…

Optimization and Control · Mathematics 2024-10-03 Nicole El Karoui , Xiaolu Tan

We study a bilevel \emph{max-max} optimization framework for principal-agent contract design, in which a principal chooses incentives to maximize utility while anticipating the agent's best response. This problem, central to moral hazard…

Machine Learning · Computer Science 2025-10-27 Tomer Galanti , Aarya Bookseller , Korok Ray

We develop the linear programming approach to mean-field games in a general setting. This relaxed control approach allows to prove existence results under weak assumptions, and lends itself well to numerical implementation. We consider…

Optimization and Control · Mathematics 2020-11-24 Roxana Dumitrescu , Marcos Leutscher , Peter Tankov

This paper is concerned with the problem of designing agents able to dynamically select information from multiple data sources in order to tackle tasks that involve tracking a target behavior while optimizing a reward. We formulate this…

Optimization and Control · Mathematics 2021-06-11 Émiland Garrabé , Giovanni Russo

To tackle the difficulties faced by both stochastic dynamic programming and scenario tree methods, we present some variational approach for numerical solution of stochastic optimal control problems. We consider two different interpretations…

Optimization and Control · Mathematics 2009-07-28 Pierre Carpentier , Guy Cohen , Anes Dallagi

The solution of a constrained linear-quadratic regulator problem is determined by the set of its optimal active sets. We propose an algorithm that constructs this set of active sets for a desired horizon N from that for horizon N-1. While…

Optimization and Control · Mathematics 2020-09-21 Ruth Mitze , Martin Mönnigmann

In this paper, we consider a problem of contract theory in which several Principals hire a common Agent and we study the model in the continuous time setting. We show that optimal contracts should satisfy some equilibrium conditions and we…

Optimization and Control · Mathematics 2018-01-15 Thibaut Mastrolia , Zhenjie Ren

In this paper, we consider discrete-time infinite horizon problems of optimal control to a terminal set of states. These are the problems that are often taken as the starting point for adaptive dynamic programming. Under very general…

Systems and Control · Computer Science 2015-10-05 Dimitri P. Bertsekas

This paper focuses on the role of a government of a large population of interacting agents as a mean field optimal control problem derived from deterministic finite agent dynamics. The control problems are constrained by a PDE of…

Analysis of PDEs · Mathematics 2020-11-17 Massimo Fornasier , Stefano Lisini , Carlo Orrieri , Giuseppe Savaré