When error reduction stagnates, a hidden unit is recruited. As the first hidden unit is added, its input weights are frozen (shown in solid arrows), and training of the output weights resumes.
	CC networks are generative in the sense that the learning algorithm builds the internal topology of a network. Thus, CC networks grow as they learn.