AIMar 18, 2017
Solving the Goddard problem by an influence diagram
arXiv:1703.06321v21 citations
AI Analysis
This work addresses a specific optimization problem in aerospace or control theory, but appears incremental as it applies an existing method to a known problem.
The authors tackled the Goddard problem by applying influence diagrams, a decision-theoretic extension of probabilistic graphical models, and compared their solutions to the optimal one in numerical experiments.
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.