Description du projet
Poser les bases de la conception future des interfaces utilisateur
Malgré la croissance rapide de l’industrie informatique et l’omniprésence de la numérisation dans divers secteurs de la vie moderne, le domaine de l’interaction Homme-Machine et des interfaces utilisateur (IU) manque encore de solutions globales. Pour répondre à ce besoin, le projet COMPUTED, financé par l’UE, vise à jeter les bases d’avancées substantielles en matière de conception d’IU. Il mettra au point un système révolutionnaire capable d’analyser et d’optimiser automatiquement les conceptions d’IU, fournissant aux développeurs des informations précieuses pour des améliorations potentielles. Ce système se distinguera par son approche révolutionnaire, tirant parti d’un soutien algorithmique parallèlement à des analyses formelles des problèmes décisionnels et à un paradigme innovant d’optimisation de l’IU. Grâce à ces efforts, COMPUTED permettra de réaliser des progrès significatifs dans le domaine de l’interaction Homme-Machine, améliorant ainsi l’expérience de l’utilisateur dans le monde du numérique.
Objectif
PROBLEM: Despite extensive research on human-computer interaction (HCI), no method exists that guarantees the optimal or even a provably good user interface (UI) design. The prevailing approach relies on heuristics and iteration, which can be costly and even ineffective, because UI design often involves combinatorially hard problems with immense design spaces, multiple objectives and constraints, and complex user behavior.
OBJECTIVES: COMPUTED establishes the foundations for optimizing UI designs. A design can be automatically optimized to given objectives and constraints by using combinatorial optimization methods that deploy predictive models of user behavior as objective functions. Although previous work has shown some improvements to usability, the scope has been restricted to keyboards and widgets. COMPUTED researches methods that can vastly expand the scope of optimizable problems. First, algorithmic support is developed for acquiring objective functions that cover the main human factors in a given HCI task. Second, formal analysis of decision problems in UI design allows combating a broader range of design tasks with efficient and appropriate optimization methods. Third, a novel interactive UI optimization paradigm for UI designers promotes fast convergence to good results even in the face of uncertainty and incomplete knowledge.
IMPACT: Combinatorial UI optimization offers a strong complement to the prevailing design approaches. Because the structured search process has a high chance of finding good solutions, optimization could improve the quality of interfaces used in everyday life. Optimization can also increase cost-efficiency, because reference to optimality can eliminate fruitless iteration. Moreover, because no preknowledge of UI design is required, even novices will be able to design great UIs. Even in “messy,” less well-defined problems, it may support designers by allowing them to delegate the solving of well-known sub-problems.
Champ scientifique
- natural sciencescomputer and information sciencesdata science
- natural sciencescomputer and information sciencesartificial intelligencemachine learningreinforcement learning
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- natural sciencescomputer and information sciencesartificial intelligenceheuristic programming
- natural sciencesmathematicsapplied mathematicsmathematical model
Programme(s)
Thème(s)
Régime de financement
ERC-STG - Starting GrantInstitution d’accueil
02150 Espoo
Finlande