Reconstruction of low-complexity control programs from data
Florent Delmotte, Magnus Egerstedt · 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601) · 2004
In this paper, we study the problem of generating control programs, i.e. strings of symbolic descriptions of control-interrupt pairs (or modes) from input-output data. In particular, we take the point of view that such control programs have an information theoretic content and thus, that they can be more or less effectively coded. As a result, we focus our attention on the problem of producing low-complexity programs by recovering the strings that contain the smallest number of distinct modes. An example is provided where the data is obtained by tracking ten roaming ants in a tank.