The strength of the system and my experiences of it, was that in fact, oddly enough, it was actually a very collaborative enterprise already

Video:35 mins, 2006. The video shows a group of performers in a studio and seminar situation. Individually addressing the camera they offer personal views and experiences of their own art production in relation to the institution, while reflecting on their role as teachers. The performance scripts mainly originate from a series of real interviews with a diverse group of artist teachers, who emphasise the collaborative, performative and subversive nature of teaching. These views may seems symptomatic for contemporary art practices, but are ultimately antagonistic to the ongoing commodification of the system of art education.

Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence

In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SI-MRLS) algorithm. The SI-MRLS algorithm applies the particle swarm optimization (PSO) to construct a flexible radial basis function (RBF) model so that both the model structure and output weights can be adapted. By replacing an insignificant RBF node with a new one based on the increment of error variance criterion at every iteration, the model remains at a limited size. The multi-innovation RLS algorithm is used to update the RBF output weights which are known to have better accuracy than the classic RLS. The proposed method can produces a parsimonious model with good performance. Simulation result are also shown to verify the SI-MRLS algorithm.