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We study an optimal control problem in which both the objective function and the dynamic constraint contain an uncertain parameter. Since the distribution of this uncertain parameter is not exactly known, the objective function is taken as…

Optimization and Control · Mathematics 2016-11-29 Jianxiong Ye , Lei Wang , Changzhi Wu , Jie Sun , Kok Lay Teo , Xiangyu Wang

The paper addresses the problem of providing suitable reference trajectories in motion planning problems for autonomous vehicles. Among the various approaches to compute a reference trajectory, our aim is to find those trajectories which…

Optimization and Control · Mathematics 2018-01-24 Matthias Gerdts , Björn Martens

This paper considers a time-varying optimization problem associated with a network of systems, with each of the systems shared by (and affecting) a number of individuals. The objective is to minimize cost functions associated with the…

Optimization and Control · Mathematics 2022-03-15 Ana M. Ospina , Andrea Simonetto , Emiliano Dall'Anese

In recent years, a range of measures of partial stochastic dominance have been introduced. These measures attempt to determine the extent to which one distribution is dominated by another. We assess these measures from intuitive, axiomatic,…

Probability · Mathematics 2024-10-01 Takashi Kamihigashi , John Stachurski

Economists often estimate economic models on data and use the point estimates as a stand-in for the truth when studying the model's implications for optimal decision-making. This practice ignores model ambiguity, exposes the decision…

Econometrics · Economics 2021-10-07 Maximilian Blesch , Philipp Eisenhauer

Fighting Fantasy is a popular recreational fantasy gaming system worldwide. Combat in this system progresses through a stochastic game involving a series of rounds, each of which may be won or lost. Each round, a limited resource (`luck')…

Artificial Intelligence · Computer Science 2020-02-25 Iain G. Johnston

The aim of this paper is to address optimality of stochastic control strategies via dynamic programming subject to total variation distance ambiguity on the conditional distribution of the controlled process. We formulate the stochastic…

Optimization and Control · Mathematics 2014-02-06 Ioannis Tzortzis , Charalambos D. Charalambous , Themistoklis Charalambous

We consider a non-stationary variant of a sequential stochastic optimization problem, in which the underlying cost functions may change along the horizon. We propose a measure, termed variation budget, that controls the extent of said…

Probability · Mathematics 2019-06-07 O. Besbes , Y. Gur , A. Zeevi

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

Stability of Wardrop equilibria is analyzed for dynamical transportation networks in which the drivers' route choices are influenced by information at multiple temporal and spatial scales. The considered model involves a continuum of…

Dynamical Systems · Mathematics 2015-03-17 Giacomo Como , Ketan Savla , Daron Acemoglu , Munther A. Dahleh , Emilio Frazzoli

For a binary choice problem, the spatial coordination of decisions in an agent community is investigated both analytically and by means of stochastic computer simulations. The individual decisions are based on different local information…

Statistical Mechanics · Physics 2009-11-07 Frank Schweitzer , Joerg Zimmermann , Heinz Muehlenbein

We consider a distribution logistics scenario where a shipping operator, managing a limited amount of resources, receives a stream of collection requests, issued by a set of customers along a booking time-horizon, that are referred to a…

Optimization and Control · Mathematics 2023-07-04 Giovanni Giallombardo , Francesca Guerriero , Giovanna Miglionico

Iterative trajectory optimization techniques for non-linear dynamical systems are among the most powerful and sample-efficient methods of model-based reinforcement learning and approximate optimal control. By leveraging time-variant local…

Systems and Control · Electrical Eng. & Systems 2019-08-01 Onur Celik , Hany Abdulsamad , Jan Peters

Recent transportation research highlights the potential of autonomous vehicles (AV) to improve traffic flow mobility as they are able to maintain smaller car-following distances. However, as a unique class of ground robots, AVs are…

Robotics · Computer Science 2025-07-09 Hangyu Li , Xiaotong Sun , Chenglin Zhuang , Xiaopeng Li

Street-level bureaucrats, such as caseworkers and border guards routinely face the dilemma of whether to follow rigid policy or exercise discretion based on professional judgement. However, frequent overrides threaten consistency and…

Computers and Society · Computer Science 2026-02-11 Gaurab Pokharel , Sanmay Das , Patrick J. Fowler

Decision making in modern stochastic systems, including e-commerce platforms, financial markets and healthcare systems, has evolved into a multifaceted process that combines information acquisition and adaptive information sources. This…

Optimization and Control · Mathematics 2026-01-07 Renyuan Xu , Thaleia Zariphopoulou , Luhao Zhang

Stochastic effects significantly influence the dynamics of traffic flows. Many dynamic traffic assignment (DTA) models attempt to capture these effects by prescribing a specific ratio that determines how flow splits across different routes…

Optimization and Control · Mathematics 2024-09-20 Lukas Graf , Tobias Harks , Michael Markl

The mean completion time of a stochastic process may be rendered finite and minimised by a judiciously chosen restart protocol, which may either be stochastic or deterministic. Here we study analytically an arbitrary stochastic search…

Quantitative Methods · Quantitative Biology 2016-09-14 Kabir Husain , Sandeep Krishna

Stochastic dominance serves as a general framework for modeling a broad spectrum of decision preferences under uncertainty, with risk aversion as one notable example, as it naturally captures the intrinsic structure of the underlying…

Machine Learning · Computer Science 2026-01-06 Shicong Cen , Jincheng Mei , Hanjun Dai , Dale Schuurmans , Yuejie Chi , Bo Dai

Rapid transit of emergency vehicles is critical for saving lives and reducing property loss but often relies on surrounding ordinary vehicles to cooperatively adjust their driving behaviors. It is important to ensure rapid transit of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 WenXi Wang , JunQi Zhang