AI

Today I finished migrating the LCS & GBML Central site from its original URL (http://lcs-gbml.ncsa.uiuc.edu) to a more permanent and stable home located at http://gbml.org. The original site is already currently redirecting the trafic to the new site, and it will be doing so for a while to help people transition and update bookmarks and feed readers. I have introduced a few changes to the functionality of the original site. Functional changes can be mostly summarized by (1) dropping the forums section and (2) closing comments on posts and pages....

Below you may find the slides of the GECCO 2009 tutorial that Jaume Bacardit and I put together. Hope you enjoy it. Slides Abstract We are living in the peta-byte era.We have larger and larger data to analyze, process and transform into useful answers for the domain experts. Robust data mining tools, able to cope with petascale volumes and/or high dimensionality producing human-understandable solutions are key on several domain areas. Genetics-based machine learning (GBML) techniques are perfect candidates for this task, among others, due to the recent advances in representations, learning paradigms, and theoretical modeling....

After coming back from GECCO I just uploaded the last of the NIGEL 2006 talks at LCS & GBML Central. This last talk was by Jaume Bacardit and GBML for protein structure prediction.

After the vacation break, two more NIGEL 2006 talks are available at LCS & GBML Central. This week Ester Bernardó presents how LCS can perform in the presence of class imbalance, whereas Lanzi continues his quest on computed predictions.

Two more NIGEL 2006 talks are available at LCS & GBML Central. This week Xavier Llorà presents how linkage learning can be achieve in Pittsburgh LCS, whereas Jorge Casillas reviews his work using XCS and Fuzzy LCS.