Genetic Programming for Smart Phone Personalisation
This addresses the need for more adaptive personalisation in smartphones for users, though it is incremental as it builds on existing genetic programming techniques.
The paper tackles the problem of insufficient adaptability in smartphone personalisation to dynamic contexts by proposing genetic programming with an Island Model, which reduces convergence time by up to two-thirds compared to standalone methods.
Personalisation in smart phones requires adaptability to dynamic context based on user mobility, application usage and sensor inputs. Current personalisation approaches, which rely on static logic that is developed a priori, do not provide sufficient adaptability to dynamic and unexpected context. This paper proposes genetic programming (GP), which can evolve program logic in realtime, as an online learning method to deal with the highly dynamic context in smart phone personalisation. We introduce the concept of collaborative smart phone personalisation through the GP Island Model, in order to exploit shared context among co-located phone users and reduce convergence time. We implement these concepts on real smartphones to demonstrate the capability of personalisation through GP and to explore the benefits of the Island Model. Our empirical evaluations on two example applications confirm that the Island Model can reduce convergence time by up to two-thirds over standalone GP personalisation.