How Single Ant ACO Systems Optimize Pseudo-Boolean Functions

Autor:	Benjamin Doerr, Daniel Johannsen, Ching Hoo Tang
Rok vydání:	2008
Předmět:	Computer science Stochastic process business.industry Evolutionary algorithm Artificial intelligence Boolean function Tracking (particle physics) business ANT
Zdroj:	Parallel Problem Solving from Nature – PPSN X ISBN: 9783540876991 PPSN
Popis:	We undertake a rigorous experimental analysis of the optimization behavior of the two most studied single ant ACO systems on several pseudo-boolean functions. By tracking the behavior of the underlying random processes rather than just regarding the resulting optimization time, we gain additional insight into these systems. A main finding is that in those cases where the single ant ACO system performs well, it basically simulates the much simpler (1+1) evolutionary algorithm.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c38a69a1056d3ade073801a08b051c55 https://doi.org/10.1007/978-3-540-87700-4_38 Zobrazit plný text záznamu