In this paper, we explore the concept of genetic structural expansion by employing a multi-stage chromosome coding scheme in a genetic algorithm (GA) based game-playing environment. Although structural expansion has been considered as a means of increasing diversity so as to benefit the GA optimization process in a changing world, it was seldom studied in the context of a multi-stage reinforced environment. This paper compares three chromosome coding schemes: monoploidy, triploidy (as a special case of polyploidy), and structural expansion, and discusses their impacts on multiple fuzzy-staged game-playing strategies. We show in this paper that when polyploid chromosomes are employed to cope with the changing environment in the domain of game-playing, the average learning result is apparently better than the learning curves in which only monoploidy is used. This piece of work is an empirical study under the Evolutionary Strategy paradigm mentioned in .
|Number of pages||5|
|State||Published - 1 Dec 1994|
|Event||Proceedings of the 1994 1st International Joint Conference of NAFIPS/IFIS/NASA - San Antonio, TX, USA|
Duration: 18 Dec 1994 → 21 Dec 1994
|Conference||Proceedings of the 1994 1st International Joint Conference of NAFIPS/IFIS/NASA|
|City||San Antonio, TX, USA|
|Period||18/12/94 → 21/12/94|