After attending Albert Orriols’s Ph.D. thesis defense, I ended wondering how many of the question I posted in mine have not been solved. The answer, quite a bit. So, I just decided to dig it up, and put it up here. Yes, the thesis was not written in English (in those days my fellowship had some strings attached), but math formulation, graphs, and results are readable in any language ;) Also, GALE was written and documented in english, and is available here.
Abstract:
This thesis combines different ideas provided by machine learning, evolutionary computation (genetics-based machine learning), and artificial life. The aim of this work is to create a data mining model that satisfies certain guidelines. The first one deals with the type of attributes that can be used in the model. The second one focuses on the goal that the model has to independent of the knowledge representation used. Finally, the model must exploit massive parallelism. Artificial Life can be very useful dealing with parallelism models.This thesis combines different ideas provided by machine learning, evolutionary computation (genetics-based machine learning), and artificial life. The aim of this work is to create a data mining model that satisfies certain guidelines. The first one deals with the type of attributes thatcan be used in the model. The second one focuses on the goal that the model has to independent of the knowledge representation used. Finally, the model must exploit massive parallelism. Artificial Life can be very useful dealing with parallelism models. [ipaper docId=3836792 access_key=key-35vxegpmvwcx3ldxpq3 height=400 width=550 /]