PRESS RELEASE: Abbadingo One Machine Learning Competition - ANNOUCEMENT CONTACT: Barak Pearlmutter, 505 277-9425, abbadingo@cs.unm.edu RELEASE DATE: MARCH 7, 1997 (REVISED: MARCH 18, 1997) Abbadingo One: DFA Learning Competition This machine learning challenge problem is aimed at anyone interested in making computers extract underlying structure from masses of data. Current machine learning techniques are inadequate to the increasing volumes of information whose structure we would like to induce, and to the increasing complexity of the underlying regularities. In order to encourage the development of algorithms that can handle larger problems, and can correctly induce more complicated things from less data, we have organized a competition. A table of twelve problems, each beyond the current state of the art, are being made publicly available. Whoever solves a previously unsolved problem harder than any solved problem (before the end of the competition on 15-Nov-1997) will receive an award of at least $1,024. We have stripped the problem down to its essentials: find the structure of a regular language (a very restricted but common class of formal languages) based on a set of training samples classified by a randomly generated deterministic finite automaton --- and demonstrate competence by classifying a set of test strings with over 99% accuracy. All of the twelve problems are identical in form, differing only in the amount of data available and the size of the target DFA. The competition is being sponsored by, among others, * The Computer Science Department at the University of New Mexico, which is providing computational support. * The prestigious Kluwer Academic journal "Machine Learning," which will give priority treatment to a paper describing the award winning algorithm. * The Santa Fe Institute, which will host the award ceremony. * The "Journal of Artificial Intelligence Research." For details retrieve http://abbadingo.cs.unm.edu/ May the best algorithms win! -- Competition organizers: Kevin J. Lang, Research Scientist, NEC Research Institute, Princeton NJ Barak A. Pearlmutter, Assistant Prof, Comp Sci Dept, Univ New Mexico