Optimal control in large stochastic multi-agent systems.
Bart Broek, Wim Wiegerinck and Bert Kappen
In: Alamas, 2-3 April 2007, The netherlands.
Abstract. We study optimal control in large stochastic multi-agent systems
in continuous space and time. We consider multi-agent systems
where agents have independent dynamics with additive noise and control.
The goal is to minimize the joint cost, which consists of a state
dependent term and a term quadratic in the control. The system is described
by a mathematical model, and an explicit solution is given. We
focus on large systems where agents have to distribute themselves over a
number of targets with minimal cost. In such a setting the optimal control
problem is equivalent to a graphical model inference problem. Exact
inference will be intractable, and we use the mean eld approximation to
compute accurate approximations of the optimal controls. We conclude
that near to optimal control in large stochastic multi-agent systems is
possible with this approach.