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In this paper, we address the problem of closed-loop control of nonlinear dynamical systems subjected to probabilistic uncertainties. More precisely, we design time-varying polynomial feedback controllers to follow the given nominal…

Optimization and Control · Mathematics 2019-12-10 Ashkan Jasour , Brian Williams

The Kelly or proportional allocation mechanism is a simple and efficient auction-based scheme that distributes an infinitely divisible resource proportionally to the agents bids. When agents are aware of the allocation rule, their…

Computer Science and Game Theory · Computer Science 2026-03-27 Younes Ben Mazziane , Cleque-Marlain Mboulou Moutoubi , Eitan Altman , Francesco De Pellegrini

We consider a class of $\ell_0$-regularized linear-quadratic (LQ) optimal control problems. This class of problems is obtained by augmenting a penalizing sparsity measure to the cost objective of the standard linear-quadratic regulator…

Optimization and Control · Mathematics 2015-07-31 MirSaleh Bahavarnia

We study the discrete-time linear-quadratic (LQ) control model using reinforcement learning (RL). Using entropy to measure the cost of exploration, we prove that the optimal feedback policy for the problem must be Gaussian type. Then, we…

Machine Learning · Statistics 2025-02-05 Lucky Li

In modern portfolio theory, the balancing of expected returns on investments against uncertainties in those returns is aided by the use of utility functions. The Kelly criterion offers another approach, rooted in information theory, that…

Risk Management · Quantitative Finance 2015-03-13 Ole Peters

In this paper we examine problems motivated by on-line financial problems and stochastic games. In particular, we consider a sequence of entirely arbitrary distinct values arriving in random order, and must devise strategies for selecting…

Data Structures and Algorithms · Computer Science 2007-05-23 Ming-Yang Kao , Stephen R. Tate

An infinite-dimensional bilinear optimal control problem with infinite-time horizon is considered. The associated value function can be expanded in a Taylor series around the equilibrium, the Taylor series involving multilinear forms which…

Optimization and Control · Mathematics 2017-09-14 Tobias Breiten , Karl Kunisch , Laurent Pfeiffer

This paper proposes a model predictive controller for discrete-time linear systems with additive, possibly unbounded, stochastic disturbances and subject to chance constraints. By computing a polytopic probabilistic positively invariant set…

Optimization and Control · Mathematics 2024-09-23 Kai Wang , Kiet Tuan Hoang , Sébastien Gros

In this paper, we study the irregular output feedback linear quadratic (LQ) control problem, which is a continuous work of previous works for irregular LQ control [33] where the state is assumed to be exactly known priori. Different from…

Optimization and Control · Mathematics 2019-05-17 Juanjuan Xu , Huanshui Zhang

This paper applies a reinforcement learning (RL) method to solve infinite horizon continuous-time stochastic linear quadratic problems, where drift and diffusion terms in the dynamics may depend on both the state and control. Based on…

Optimization and Control · Mathematics 2021-09-17 Na Li , Xun Li , Jing Peng , Zuo Quan Xu

In evaluating prediction markets (and other crowd-prediction mechanisms), investigators have repeatedly observed a so-called "wisdom of crowds" effect, which roughly says that the average of participants performs much better than the…

Artificial Intelligence · Computer Science 2012-02-01 Alina Beygelzimer , John Langford , David Pennock

We study the incremental knapsack problem, where one wishes to sequentially pack items into a knapsack whose capacity expands over a finite planning horizon, with the objective of maximizing time-averaged profits. While various…

Data Structures and Algorithms · Computer Science 2020-10-16 Ali Aouad , Danny Segev

We discretize a risk-neutral optimal control problem governed by a linear elliptic partial differential equation with random inputs using a Monte Carlo sample-based approximation and a finite element discretization, yielding finite…

Optimization and Control · Mathematics 2023-11-10 Johannes Milz

Many applications require solving non-linear control problems that are classically not well behaved. This paper develops a simple and efficient chattering algorithm that learns near optimal decision policies through an open-loop feedback…

Machine Learning · Computer Science 2017-03-21 Peeyush Kumar , Wolf Kohn , Zelda B. Zabinsky

We propose a novel reformulation of the stochastic optimal control problem as an approximate inference problem, demonstrating, that such a interpretation leads to new practical methods for the original problem. In particular we characterise…

Machine Learning · Computer Science 2010-09-22 Konrad Rawlik , Marc Toussaint , Sethu Vijayakumar

This paper considers a time-varying game with $N$ players. Every time slot, players observe their own random events and then take a control action. The events and control actions affect the individual utilities earned by each player. The…

Computer Science and Game Theory · Computer Science 2014-02-04 Michael J. Neely

This paper studies a continuous-time optimal portfolio selection problem in the complete market for a behavioral investor whose preference is of the prospect type with probability distortion. The investor concerns about the terminal…

Portfolio Management · Quantitative Finance 2022-11-11 Jing Peng , Pengyu Wei , Zuo Quan Xu

For independent multi-outcome events under multiplicative parlay pricing, we give a short exact proof of the optimal Kelly strategy using the implicit-cash viewpoint. The proof is entirely eventwise. One first solves each event in…

Optimization and Control · Mathematics 2026-03-30 Christopher D. Long

Financial markets, with their vast range of different investment opportunities, can be seen as a system of many different simultaneous games with diverse and often unknown levels of risk and reward. We introduce generalizations to the…

Portfolio Management · Quantitative Finance 2008-12-10 Matus Medo , Yury M. Pis'mak , Yi-Cheng Zhang

This work focuses on numerical solutions of optimal control problems. A time discretization error representation is derived for the approximation of the associated value function. It concerns Symplectic Euler solutions of the Hamiltonian…

Optimization and Control · Mathematics 2016-02-23 Jesper Karlsson , Stig Larsson , Mattias Sandberg , Anders Szepessy , Raùl Tempone
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