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We present an extension of two policy-iteration based algorithms on weighted graphs (viz., Markov Decision Problems and Max-Plus Algebras). This extension allows us to solve the following inverse problem: considering the weights of the…

Discrete Mathematics · Computer Science 2009-11-18 Laurent Fribourg , Etienne André

We present an anytime algorithm which computes policies for decision problems represented as multi-stage influence diagrams. Our algorithm constructs policies incrementally, starting from a policy which makes no use of the available…

Artificial Intelligence · Computer Science 2013-02-01 Michael C. Horsch , David L. Poole

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

In an incomplete market driven by time-changed L\'evy noises we consider the problem of hedging a financial position coupled with the underlying risk of model uncertainty. Then we study hedging under worst-case-scenario. The proposed…

Probability · Mathematics 2015-05-15 Giulia Di Nunno , Erik Hove Karlsen

Inferring unknown constraints is a challenging and crucial problem in many robotics applications. When only expert demonstrations are available, it becomes essential to infer the unknown domain constraints to deploy additional agents…

Robotics · Computer Science 2023-12-06 Dimitris Papadimitriou , Jingqi Li

Bayesian models quantify uncertainty and facilitate optimal decision-making in downstream applications. For most models, however, practitioners are forced to use approximate inference techniques that lead to sub-optimal decisions due to…

Machine Learning · Statistics 2019-09-12 Tomasz Kuśmierczyk , Joseph Sakaya , Arto Klami

In the knapsack problem under explorable uncertainty, we are given a knapsack instance with uncertain item profits. Instead of having access to the precise profits, we are only given uncertainty intervals that are guaranteed to contain the…

Data Structures and Algorithms · Computer Science 2025-07-04 Jens Schlöter

In real applications, database systems should be able to manage and process data with uncertainty. Any real dataset may have missing or rounded values, also the values of data may change by time. So, it becomes important to handle these…

Computational Geometry · Computer Science 2020-06-12 Sharareh Alipour

In this paper we consider the minimization of a continuous function that is potentially not differentiable or not twice differentiable on the boundary of the feasible region. By exploiting an interior point technique, we present first- and…

Computational Complexity · Computer Science 2017-02-15 Gabriel Haeser , Hongcheng Liu , Yinyu Ye

We consider an expected utility maximization problem where the utility function is not necessarily concave and the time horizon is uncertain. We establish a necessary and sufficient condition for the optimality for general non-concave…

Portfolio Management · Quantitative Finance 2021-10-14 Christian Dehm , Thai Nguyen , Mitja Stadje

In this paper we solve the hedge fund manager's optimization problem in a model that allows for investors to enter and leave the fund over time depending on its performance. The manager's payoff at the end of the year will then depend not…

Portfolio Management · Quantitative Finance 2014-03-04 Moritz Duembgen , L. C. G. Rogers

We study a robust utility maximization problem in a general discrete-time frictionless market under quasi-sure no-arbitrage. The investor is assumed to have a random and concave utility function defined on the whole real-line. She also…

Mathematical Finance · Quantitative Finance 2024-02-28 Laurence Carassus , Massinissa Ferhoune

This paper presents a new prediction model for time series data by integrating a time-varying Geometric Brownian Motion model with a pricing mechanism used in financial engineering. Typical time series models such as Auto-Regressive…

Applications · Statistics 2020-01-01 Abdullah AlShelahi , Jingxing Wang , Mingdi You , Eunshin Byon , Romesh Saigal

This paper considers the portfolio management problem of optimal investment, consumption and life insurance. We are concerned with time inconsistency of optimal strategies. Natural assumptions, like different discount rates for consumption…

Optimization and Control · Mathematics 2011-07-25 Ivar Ekeland , Oumar Mbodji , Traian A. Pirvu

We introduce a general framework for Markov decision problems under model uncertainty in a discrete-time infinite horizon setting. By providing a dynamic programming principle we obtain a local-to-global paradigm, namely solving a local,…

Optimization and Control · Mathematics 2023-01-06 Ariel Neufeld , Julian Sester , Mario Šikić

We consider the problem of decision-making under uncertainty in an environment with safety constraints. Many business and industrial applications rely on real-time optimization to improve key performance indicators. In the case of unknown…

Machine Learning · Computer Science 2023-01-31 Buse Sibel Korkmaz , Marta Zagórowska , Mehmet Mercangöz

This paper addresses the challenge of model uncertainty in quantitative finance, where decisions in portfolio allocation, derivative pricing, and risk management rely on estimating stochastic models from limited data. In practice, the…

Computational Finance · Quantitative Finance 2025-06-10 Hans Buehler , Blanka Horvath , Yannick Limmer , Thorsten Schmidt

We address a general optimal switching problem over finite horizon for a stochastic system described by a differential equation driven by Brownian motion. The main novelty is the fact that we allow for infinitely many modes (or regimes,…

Optimization and Control · Mathematics 2019-08-07 Marco Fuhrman , Marie-Amélie Morlais

In this article we study an optimal stopping/optimal control problem which models the decision facing a risk-averse agent over when to sell an asset. The market is incomplete so that the asset exposure cannot be hedged. In addition to the…

Portfolio Management · Quantitative Finance 2008-12-10 Vicky Henderson , David Hobson

We study the problem of choosing optimal policy rules in uncertain environments using models that may be incomplete and/or partially identified. We consider a policymaker who wishes to choose a policy to maximize a particular counterfactual…

Econometrics · Economics 2020-12-22 Thomas M. Russell
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