Abstract:
Traditionally, in the Osipov – Lanchester models, which describe the dynamics of the number of combatants in terms of differential equations, the combat effectiveness of the parties is considered constant over time. In this paper, we consider the role of learning in modifying the linear and quadratic Osipov – Lanchester models, taking into account two effects: a one-shot introduction of a trained reserve by the initially losing party and the acquisition of combat experience by the parties, which affects the combat effectiveness coefficients. The problems of determining the optimal moment for introducing such a reserve so that its size is minimal, but ensures a "parity"; finding the minimum learning rate of the initially losing party, also ensuring a "parity"; and determining the optimal duration of reserve training before its input, are solved.
Fulltext:
PDF file (750 kB)