User models in dialog systems
Neural network design
Adaptive Probabilistic Networks with Hidden Variables
Machine Learning - Special issue on learning with probabilistic representations
Crowds: anonymity for Web transactions
ACM Transactions on Information and System Security (TISSEC)
Fuzzy adaptive scheduling and control systems
Fuzzy Sets and Systems
Optimizing Web Page Layout Using an Annealed Genetic Algorithm as Client-Side Script
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Towards Zero-Input Personalization: Referrer-Based Page Prediction
AH '00 Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
An Architecture for Dynamical News Providers
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
Interactive dynamic production by genetic algorithms
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
An evolutionary algorithm for adaptive online services in dynamic environment
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
| Hi-index | 0.00 |
This paper present an architecture based on evolutionary 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 to model 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.