Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/838

 Title: Online Genetic Algorithms Authors: Milani, Alfredo Keywords: Genetic AlgorithmsAdaptive WebEvolutionary Computation Issue Date: 2004 Publisher: Institute of Information Theories and Applications FOI ITHEA Abstract: This paper present a technique based on genetic algorithms for generating online adaptive services. Online adaptive systems provide flexible services to a mass of clients/users for maximising some system goals, they dynamically adapt the form and the content of the issued services while the population of clients evolve over time. The idea of online genetic algorithms (online GAs) is to use the online clients response behaviour as a fitness function in order to produce the next generation of services. The principle implemented in online GAs, “the application environment is the fitness”, allow modelling highly evolutionary domains where both services providers and clients change and evolve over time. The flexibility and the adaptive behaviour of this approach seems to be very relevant and promising for applications characterised by highly dynamical features such as in the web domain (online newspapers, e- markets, websites and advertising engines). Nevertheless the proposed technique has a more general aim for application environments characterised by a massive number of anonymous clients/users which require personalised services, such as in the case of many new IT applications. URI: http://hdl.handle.net/10525/838 ISSN: 1313-0463 Appears in Collections: Volume 11 Number 1

Files in This Item:

File Description SizeFormat