Convex programming in optimal control and information theory

12/13/2017
by   Tobias Sutter, et al.
0

The main theme of this thesis is the development of computational methods for classes of infinite-dimensional optimization problems arising in optimal control and information theory. The first part of the thesis is concerned with the optimal control of discrete-time continuous space Markov decision processes (MDP). The second part is centred around two fundamental problems in information theory that can be expressed as optimization problems: the channel capacity problem as well as the entropy maximization subject to moment constraints.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/07/2019

From Reinforcement Learning to Optimal Control: A unified framework for sequential decisions

There are over 15 distinct communities that work in the general area of ...
research
12/15/2022

Morse index and determinant of block Jacobi matrices via optimal control

We describe the relation between block Jacobi matrices and minimization ...
research
11/29/2022

Performance Evaluation, Optimization and Dynamic Decision in Blockchain Systems: A Recent Overview

With rapid development of blockchain technology as well as integration o...
research
07/08/2020

On Entropic Optimization and Path Integral Control

This article is motivated by the question whether it is possible to solv...
research
05/07/2020

An Optimal Control Theory for the Traveling Salesman Problem and Its Variants

We show that the traveling salesman problem (TSP) and its many variants ...
research
06/13/2022

Markov Decision Processes under Model Uncertainty

We introduce a general framework for Markov decision problems under mode...
research
07/06/2016

Mixed Strategy for Constrained Stochastic Optimal Control

Choosing control inputs randomly can result in a reduced expected cost i...

Please sign up or login with your details

Forgot password? Click here to reset