Genetic Programming for Smart Phone Personalisation

TL;DR

This paper introduces a genetic programming approach for real-time, adaptive smartphone personalization, utilizing a collaborative Island Model to improve convergence speed by sharing context among users.

Contribution

It presents a novel online learning method using genetic programming for dynamic smartphone personalization and introduces a collaborative Island Model to enhance convergence speed.

Findings

Island Model reduces convergence time by up to two-thirds.

GP-based personalization adapts effectively to dynamic contexts.

Real smartphone implementation demonstrates practical viability.

Abstract

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.