Title :
Mutation buffering capabilities of the hypernetwork model
Author :
Segovia-Juárez, José L. ; Colombano, Silvano
Author_Institution :
Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA
Abstract :
The hypernetwork is a molecular interaction-based model that has learning capabilities. The adaptive algorithm randomly changes the molecular structures and selects the best individual. Experiments with the hypernetwork show the importance for evolution of the mutation buffering capabilities of the system. Mutation buffering allows the system to improve its search for peaks in the fitness landscape
Keywords :
biocomputing; learning (artificial intelligence); adaptive algorithm; fitness landscape; hypernetwork model; learning; molecular interaction-based model; mutation buffering; mutation buffering capabilities; Biological system modeling; Biological systems; Biology computing; Computer science; Distributed computing; Evolution (biology); Genetic mutations; Hardware; Organisms; Proteins;
Conference_Titel :
Evolvable Hardware, 2001. Proceedings. The Third NASA/DoD Workshop on
Conference_Location :
Long Beach, CA
Print_ISBN :
0-7695-1180-5
DOI :
10.1109/EH.2001.937941
