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We propose a novel distribution-free scheme to solve optimization problems where the goal is to minimize the expected value of a cost function subject to probabilistic constraints. Unlike standard sampling-based methods, our idea consists…

Optimization and Control · Mathematics 2025-05-28 Francesco Cordiano , Matin Jafarian , Bart De Schutter

We consider the problem of learning control policies that optimize a reward function while satisfying constraints due to considerations of safety, fairness, or other costs. We propose a new algorithm, Projection-Based Constrained Policy…

Machine Learning · Computer Science 2020-10-08 Tsung-Yen Yang , Justinian Rosca , Karthik Narasimhan , Peter J. Ramadge

This paper introduces a new class of optimal switching problems, where the player is allowed to switch at a sequence of exogenous Poisson arrival times, and the underlying switching system is governed by an infinite horizon backward…

Probability · Mathematics 2014-03-07 Gechun Liang , Wei Wei

We derive the explicit solutions to singular stochastic control problems of the monotone follower type with (a) an expected discounted criterion, (b) an expected ergodic criterion and (c) a pathwise ergodic criterion. These problems have…

Optimization and Control · Mathematics 2025-02-05 Gechun Liang , Zhesheng Liu , Mihail Zervos

In a classical optimal stopping problem the aim is to maximize the expected value of a functional of a diffusion evaluated at a stopping time. This note considers optimal stopping problems beyond this paradigm. We study problems in which…

Probability · Mathematics 2017-08-04 Vicky Henderson , David Hobson , Matthew Zeng

When randomness in demand affects the sales of a product, retailers use dynamic pricing strategies to maximize their profits. In this article, we formulate the pricing problem as a continuous-time stochastic optimal control problem and find…

Optimization and Control · Mathematics 2019-03-13 Asbjørn Nilsen Riseth

We consider the bail-out optimal dividend problem under fixed transaction costs for a L\'evy risk model. Furthermore, we consider the version with a constraint expected net present value of injected capital. To characterize the solution to…

Probability · Mathematics 2018-09-19 Mauricio Junca , Harold Moreno-Franco , José Luis Pérez

We investigate the optimal reinsurance problem under the criterion of maximizing the expected utility of terminal wealth when the insurance company has restricted information on the loss process. We propose a risk model with claim arrival…

Mathematical Finance · Quantitative Finance 2020-05-15 Matteo Brachetta , Claudia Ceci

A standard objective in partially-observable Markov decision processes (POMDPs) is to find a policy that maximizes the expected discounted-sum payoff. However, such policies may still permit unlikely but highly undesirable outcomes, which…

Artificial Intelligence · Computer Science 2017-01-31 Krishnendu Chatterjee , Petr Novotný , Guillermo A. Pérez , Jean-François Raskin , Đorđe Žikelić

In an equity market model with "Knightian" uncertainty regarding the relative risk and covariance structure of its assets, we characterize in several ways the highest return relative to the market that can be achieved using nonanticipative…

Probability · Mathematics 2012-02-15 Daniel Fernholz , Ioannis Karatzas

We investigate the optimal investment-reinsurance problem for insurance company with partial information on the market price of the risk. Through the use of filtering techniques we convert the original optimization problem involving…

Portfolio Management · Quantitative Finance 2024-08-15 Claudia Ceci , Katia Colaneri

In this paper we investigate a new class of growth rate maximization problems based on impulse control strategies such that the average number of trades per time unit does not exceed a fixed level. Moreover, we include proportional…

Portfolio Management · Quantitative Finance 2013-06-10 Sören Christensen , Marc Wittlinger

We consider a continuous time two-armed bandit problem in which incomes are described by Poissonian processes. We develop Bayesian approach with arbitrary prior distribution. We present two versions of recursive equation for determination…

Statistics Theory · Mathematics 2019-07-16 Alexander Kolnogorov

In this manuscript we consider the dual risk model with financial application, where the random gains occur under a renewal process. We particularly work the Erlang(n) case for common distribution of the inter-arrival times, from there it…

We consider a singular control problem that aims to maximize the expected cumulative rewards, where the instantaneous returns depend on the state of a controlled process. The contributions of this paper are twofold. Firstly, to establish…

Optimization and Control · Mathematics 2025-06-23 Mauricio Junca , Harold Moreno-Franco , Jose Luis Perez

We consider an optimal stopping problem with n correlated offers where the goal is to design a (randomized) stopping strategy that maximizes the expected value of the offer in the sequence at which we stop. Instead of assuming to know the…

Optimization and Control · Mathematics 2025-07-08 Pieter Kleer , Daan Noordenbos

We consider a piecewise deterministic Markov decision process, where the expected exponential utility of total (nonnegative) cost is to be minimized. The cost rate, transition rate and post-jump distributions are under control. The state…

Optimization and Control · Mathematics 2017-11-22 Xin Guo , Yi Zhang

We derive a variational formula for the optimal growth rate of reward in the infinite horizon risk-sensitive control problem for discrete time Markov decision processes with compact metric state and action spaces, extending a formula of…

Optimization and Control · Mathematics 2015-01-06 Venkatachalam Anantharam , Vivek Shripad Borkar

We study a stochastic optimal control problem for jump-diffusion systems whose drift coefficient is piecewise Lipschitz continuous and exhibits threshold-induced discontinuities. Such dynamics naturally arise in applications with…

Optimization and Control · Mathematics 2026-05-08 Antoine-Marie Bogso , Edward Fuituh Kameh , Olivier Menoukeu-Pamen , Felix Shu

Selective labels are a common feature of consequential decision-making applications, referring to the lack of observed outcomes under one of the possible decisions. This paper reports work in progress on learning decision policies in the…

Machine Learning · Computer Science 2020-11-04 Dennis Wei