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 maximizing some system goals; they dynamically adapt the form and the content ofthe 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 behavior 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 to model highly evolutionary domains where both services providers and clients change and evolve over time. The flexibility and the adaptive behavior of this approach seems to be very relevant and promising for applications characterized 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 characterized by a massive number of anonymous clients/users which require personalized services, such as in the case of many new IT applications.
Evolutionary online services
MILANI, Alfredo;SURIANI, SILVIA;MARCUGINI, Stefano
2005
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 maximizing some system goals; they dynamically adapt the form and the content ofthe 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 behavior 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 to model highly evolutionary domains where both services providers and clients change and evolve over time. The flexibility and the adaptive behavior of this approach seems to be very relevant and promising for applications characterized 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 characterized by a massive number of anonymous clients/users which require personalized services, such as in the case of many new IT applications.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
