Solving the Goddard problem by an influence diagram

TL;DR

This paper demonstrates how influence diagrams, a decision-theoretic graphical model, can be applied to solve the Goddard problem, providing a novel approach and comparing it with optimal solutions through numerical experiments.

Contribution

The paper introduces the use of influence diagrams for solving the Goddard problem, showcasing their effectiveness through numerical experiments and comparison with optimal solutions.

Findings

Influence diagrams can effectively solve the Goddard problem.

Solutions obtained via influence diagrams are comparable to optimal solutions.

Numerical experiments validate the approach.

Abstract

Influence diagrams are a decision-theoretic extension of probabilistic graphical models. In this paper we show how they can be used to solve the Goddard problem. We present results of numerical experiments with this problem and compare the solutions provided by influence diagrams with the optimal solution.