Training Possibilities in Cpn

Flexible production systems require usage of mobile transportation robots. Training of these robots is necessary to ensure effective and conflict less operation. The principles of multi-agent systems and artificial neural nets may be used in training processes, but some not solved yet problems make usage of these methods complicated. Colored Petri nets are well suited for purposes of training, if extension of usage of global variables made. Presence of these variables creates the possibility to accumulate data obtained during training and provide databases. The training of system is conducted on the model; collisions are resolved using graphical subsystem and database, accessible for all mobile robots, provided. The database of the already trained system of control can be transferred to the control device.