R.Rayyes has presented our recent work at Intrinsically Motivated Open-ended Learning (IMOL). The presented work highlights the first associative dynamic network to be constructed from scratch and updated continuously online for learning kinematics with redundancy. The dynamic network demonstrates high stability and its complexity is tailored to the learned functions. Moreover, the work also proposes online interest-based exploration where the curiosity measure is updated on the fly.