REGAL:

REGAL (RElational Genetic Algorithm Learner) is a distributed GA-based system, designed for learning multi-modal First Order Logic concept descriptions from examples. REGAL is based on a SELECTION operator, called Universal Suffrage operator, provably allowing the POPULATION to asymptotically converge, on average, to an equilibrium state, in which several SPECIES coexist. REGAL makes use of PVM 3.3 and Tcl/Tk. This version of REGAL is provided with a graphical user interface developed in Tcl/Tk language.

REGAL has been jointly developed by: Attilio Giordana <attilio@di.unito.it> http://www.di.unito.it/~attilio/ and Filippo Neri <neri@di.unito.it> http://www.di.unito.it/~neri/ at the University of Torino, Dipartimento di Informatica, Italy.

See also:

Neri F. and Giordana A. (1995). "A Distributed Genetic Algorithm for Concept Learning", Proc. Int. Conf. on Genetic Algorithms (Pittsburgh, PA), Morgan Kaufmann, pp. 436-443.

Neri F. and Saitta L. (1995). "A Formal Analysis of Selection Schemes". Proc. Int. Conf. on Genetic Algorithms (Pittsburgh,PA), Morgan Kaufmann, pp. 32-39 .

Giordana A. and Neri F. (1996). "Search-Intensive Concept Induction". Evolutionary Computation Journal, MIT Press, vol. 3, n. 4, pp. 375 - 416.

Neri F. and Saitta L. (1997). "An Analysis of the Universal Suffrage Selection Operator". Evolutionary Computation Journal, MIT Press, vol. 4, n. 1, pp. 89-109.