TY - GEN
T1 - Mean-field games with logistic population dynamics
AU - Gomes, Diogo A.
AU - Ribeiro, Ricardo de Lima
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2013/12
Y1 - 2013/12
N2 - In its standard form, a mean-field game can be defined by coupled system of equations, a Hamilton-Jacobi equation for the value function of agents and a Fokker-Planck equation for the density of agents. Traditionally, the latter equation is adjoint to the linearization of the former. Since the Fokker-Planck equation models a population dynamic, we introduce natural features such as seeding and birth, and nonlinear death rates. In this paper we analyze a stationary meanfield game in one dimension, illustrating various techniques to obtain regularity of solutions in this class of systems. In particular we consider a logistic-type model for birth and death of the agents which is natural in problems where crowding affects the death rate of the agents. The introduction of these new terms requires a number of new ideas to obtain wellposedness. In a forthcoming publication we will address higher dimensional models. ©2013 IEEE.
AB - In its standard form, a mean-field game can be defined by coupled system of equations, a Hamilton-Jacobi equation for the value function of agents and a Fokker-Planck equation for the density of agents. Traditionally, the latter equation is adjoint to the linearization of the former. Since the Fokker-Planck equation models a population dynamic, we introduce natural features such as seeding and birth, and nonlinear death rates. In this paper we analyze a stationary meanfield game in one dimension, illustrating various techniques to obtain regularity of solutions in this class of systems. In particular we consider a logistic-type model for birth and death of the agents which is natural in problems where crowding affects the death rate of the agents. The introduction of these new terms requires a number of new ideas to obtain wellposedness. In a forthcoming publication we will address higher dimensional models. ©2013 IEEE.
UR - http://hdl.handle.net/10754/564832
UR - http://ieeexplore.ieee.org/document/6760258/
UR - http://www.scopus.com/inward/record.url?scp=84902324374&partnerID=8YFLogxK
U2 - 10.1109/CDC.2013.6760258
DO - 10.1109/CDC.2013.6760258
M3 - Conference contribution
SN - 9781467357173
SP - 2513
EP - 2518
BT - 52nd IEEE Conference on Decision and Control
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -