On a Boltzmann mean field model for knowledge growth

Martin Burger (1) , Alexander Lorz (2, 3) , Marie-Therese Wolfram (4)

1 WWU - Westfälische Wilhelms-Universität Münster = University of Münster
2 MAMBA - Modelling and Analysis for Medical and Biological Applications
3 LJLL - Laboratoire Jacques-Louis Lions
4 Faculty of Mathematics [Vienna]

In this paper we analyze a Boltzmann type mean field game model for knowledge growth, which was proposed by Lucas and Moll [14]. We discuss the underlying mathematical model, which consists of a coupled system of a Boltzmann type equation for the agent density and a Hamilton-Jacobi-Bellman equation for the optimal strategy. We study the analytic features of each equation separately and show local in time existence and uniqueness for the fully coupled system. Furthermore we focus on the construction and existence of special solutions, which relate to exponential growth in time-so called balanced growth path solutions. Finally we illustrate the behavior of solutions for the full system and the balanced growth path equations with numerical simulations.

Domaines: Equations aux dérivées partielles [math.AP]

Martin Burger, Alexander Lorz, Marie-Therese Wolfram. On a Boltzmann mean field model for knowledge growth . SIAM Journal on Applied Mathematics, 2016, ⟨10.1137/15M1018599⟩. ⟨hal-01163491⟩