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We consider the problem of trajectory planning in an environment comprised of a set of obstacles with uncertain locations. While previous approaches model the uncertainties with a prescribed Gaussian distribution, we consider the realistic…

Systems and Control · Computer Science 2021-01-12 Vasileios Lefkopoulos , Maryam Kamgarpour

In this paper, we derive explicit closed-form solutions for the value function and the associated optimal stopping boundaries in an optimal annuitization problem under a mortality shock. We consider an individual whose retirement wealth is…

Mathematical Finance · Quantitative Finance 2026-04-13 Matteo Buttarazzi

The exploration-exploitation trade-off is among the central challenges of reinforcement learning. The optimal Bayesian solution is intractable in general. This paper studies to what extent analytic statements about optimal learning are…

Machine Learning · Statistics 2015-03-13 Philipp Hennig

We study a consumption-investment problem in a multi-asset market where the returns follow a generic rank-based model. Our main result derives an HJB equation with Neumann boundary conditions for the value function and proves a…

Mathematical Finance · Quantitative Finance 2025-10-24 David Itkin

In this paper, we propose a probabilistic game-theoretic model to study the properties of the worst-case regret of the greedy strategy under complete (Knightian) uncertainty. In a game between a decision-maker (DM) and an adversarial agent…

Computer Science and Game Theory · Computer Science 2025-02-12 Kristijan Atanasov , Mehmet Ismail , Frederik Mallmann-Trenn

We introduce a novel equilibrium concept that incorporates Knightian uncertainty into the cursed equilibrium (Eyster and Rabin, 2005). This concept is then applied to a two-player game in which agents can engage in trade or refuse to do so.…

Theoretical Economics · Economics 2025-06-13 Jurek Preker

In this paper we analyse a dynamic model of investment under uncertainty in a duopoly, in which each firm has an option to switch from the present market to a new market. We construct a subgame perfect equilibrium in mixed strategies and…

Economics · Quantitative Finance 2015-06-16 Jan-Henrik Steg , Jacco Thijssen

Recent advances in reconstruction methods for inverse problems leverage powerful data-driven models, e.g., deep neural networks. These techniques have demonstrated state-of-the-art performances for several imaging tasks, but they often do…

Computer Vision and Pattern Recognition · Computer Science 2020-10-20 Riccardo Barbano , Chen Zhang , Simon Arridge , Bangti Jin

We study the problem of maximising terminal utility for an agent facing model uncertainty, in a frictionless discrete-time market with one safe asset and finitely many risky assets. We show that an optimal investment strategy exists if the…

Mathematical Finance · Quantitative Finance 2020-07-10 Miklós Rásonyi , Andrea Meireles-Rodrigues

We consider optimal stopping problems for a Brownian motion and a geometric Brownian motion with a "disorder", assuming that the moment of a disorder is uniformly distributed on a finite interval. Optimal stopping rules are found as the…

Statistics Theory · Mathematics 2012-12-18 A. N. Shiryaev , M. V. Zhitlukhin

We consider the problem of sequentially making decisions that are rewarded by "successes" and "failures" which can be predicted through an unknown relationship that depends on a partially controllable vector of attributes for each instance.…

Machine Learning · Statistics 2017-09-18 Yingfei Wang , Chu Wang , Warren Powell

We investigate an optimal control problem motivated by neuroscience, where the dynamics is driven by a Poisson process with a controlled stochastic intensity and an unknown parameter. Given a prior distribution for the unknown parameter, we…

Optimization and Control · Mathematics 2025-12-23 Nicolas Baradel , Quentin Cormier

In this paper we study an incomplete information optimal switching problem in which the manager only has access to noisy observations of the underlying Brownian motion $\{W_t\}_{t \geq 0}$. The manager can, at a fixed cost, switch between…

Optimization and Control · Mathematics 2015-03-18 Marcus Olofsson

We explore reinforcement learning methods for finding the optimal policy in the linear quadratic regulator (LQR) problem. In particular, we consider the convergence of policy gradient methods in the setting of known and unknown parameters.…

Machine Learning · Computer Science 2021-06-25 Ben Hambly , Renyuan Xu , Huining Yang

Existing observational approaches for learning human preferences, such as inverse reinforcement learning, usually make strong assumptions about the observability of the human's environment. However, in reality, people make many important…

Machine Learning · Statistics 2021-10-29 Cassidy Laidlaw , Stuart Russell

We consider the problem of learning optimal solutions of a partially known linear optimization problem and recovering its underlying cost function where a set of past decisions and the feasible set are known. We develop a new framework,…

Optimization and Control · Mathematics 2023-01-10 Farzin Ahmadi , Fardin Ganjkhanloo , Kimia Ghobadi

We propose a general framework for studying optimal issue of CAT bonds in the presence of uncertainty on the parameters. In particular, the intensity of arrival of natural disasters is inhomogeneous and may depend on unknown parameters.…

Optimization and Control · Mathematics 2024-05-06 Nicolas Baradel

Finding Bertram's optimal trading strategy for a pair of cointegrated assets following the Ornstein--Uhlenbeck price difference process can be formulated as an unconstrained convex optimization problem for maximization of expected profit…

Mathematical Finance · Quantitative Finance 2022-11-23 Vladimír Holý , Michal Černý

We propose an algorithm to calculate the exact solution for utility optimization problems on finite state spaces under a class of non-differentiable preferences. We prove that optimal strategies must lie on a discrete grid in the plane, and…

Pricing of Securities · Quantitative Finance 2018-10-01 Marcellino Gaudenzi , Michel Vellekoop

Insider information and model uncertainty are two unavoidable problems for the portfolio selection theory in reality. This paper studies the robust optimal portfolio strategy for an investor who owns general insider information under model…

Numerical Analysis · Mathematics 2022-07-11 Chao Yu , Yuhan Cheng