Project description
Setting the foundations for future user interface design
Despite the rapid growth of the computer industry and the pervasive digitalisation in various sectors of modern life, the field of computer-human interaction and user interfaces (UIs) still lacks comprehensive solutions. Addressing this need, the EU-funded COMPUTED project aims to lay the groundwork for substantial advancements in UI design. It will develop a ground-breaking system that can automatically analyse and optimise UI designs, providing developers with valuable insights for potential enhancements. This system will stand out for its revolutionary approach, leveraging algorithmic support alongside formal analyses of decision problems and an innovative UI optimisation paradigm. Through these efforts, COMPUTED will drive significant progress in the field of computer human interaction, ultimately enhancing the user experience in the digital realm.
Objective
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.
Fields of science
- 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
Keywords
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Funding Scheme
ERC-STG - Starting GrantHost institution
02150 Espoo
Finland