> > > > Is there any research that can tell us what kind of structures are better > for machine learning? Or perhaps w.r.t a certain type of data? Are there > learning structures that will somehow "learn things faster"? >
There is plenty of knowledge about which learning algorithms are better for which problem classes. For example, there are problems known to be deceptive (not efficiently solved) for genetic programming, yet that are known to be efficiently solvable by MOSES, the probabilistic program learning method used in Novamente (from Moshe Looks' PhD thesis, see metacog.org) > > Note that, if the answer is negative, then the choice of learning > structures is arbitrary and we should choose the most developed / heavily > researched ones (such as first-order logic). > > The choice is not at all arbitrary; but the knowledge we have to guide the choice is currently very incomplete. So one has to make the right intuitive choice based on integrating the available information. This is part of why AGI is hard at the current level of development of computer science. -- Ben G ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=8660244&id_secret=62863431-4f3cc5
