A Robust Decision Making Framework for Optimal Strategy Selection in Warfare under Model Uncertainty
Optimization and Control
2022-07-05 v1
Abstract
In this paper is presented a framework for treating uncertainty in optimal decision problems occuring in combat situations, in order to robustly select the optimal strategy. A stochastic version of the popular Lanchester's aimed-fire model is considered as the underlying combat system describing the combet dynamics, and upon this an optimal decision rule for allocating forces is constructed. This approach results to a very extendable optimal decision framework, where the optimal strategy is chosen by simultaneously treating robustly uncertainty regarding critical combat parameters.
Cite
@article{arxiv.2207.00861,
title = {A Robust Decision Making Framework for Optimal Strategy Selection in Warfare under Model Uncertainty},
author = {Georgios I. Papayiannis},
journal= {arXiv preprint arXiv:2207.00861},
year = {2022}
}