4:00 PM-6:00 PM
Orchard & Pikake (Salon 7 & 8)
Stochastic approximation algorithms are discrete time stochastic processes arising in many applications. Sample paths {xk} are closely related to trajectories of the mean vector field F(x) := (k+1) E (xk+1 - xk/ xk = x) . Tools of deterministic dynamics, such as attractors and chain recurrence, yield information on the limit set of {xk}, sometimes proving almost sure convergence (or nonconvergence). Benaïm will introduce the subject; Hirsch and Schreiber will discuss Game Theory and Evolutionary Processes; Kushner will present estimates of convergence rates. This minisymposium should interest researchers in probability, differential equations, game theory and population dynamics.
Organizers: Michel Benaïm