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Mobile User Interface Adaptation Based on Usability Reward Model and Multi-Agent Reinforcement Learning.
- Source :
- Multimodal Technologies & Interaction; Apr2024, Vol. 8 Issue 4, p26, 21p
- Publication Year :
- 2024
-
Abstract
- Today, reinforcement learning is one of the most effective machine learning approaches in the tasks of automatically adapting computer systems to user needs. However, implementing this technology into a digital product requires addressing a key challenge: determining the reward model in the digital environment. This paper proposes a usability reward model in multi-agent reinforcement learning. Well-known mathematical formulas used for measuring usability metrics were analyzed in detail and incorporated into the usability reward model. In the usability reward model, any neural network-based multi-agent reinforcement learning algorithm can be used as the underlying learning algorithm. This paper presents a study using independent and actor-critic reinforcement learning algorithms to investigate their impact on the usability metrics of a mobile user interface. Computational experiments and usability tests were conducted in a specially designed multi-agent environment for mobile user interfaces, enabling the implementation of various usage scenarios and real-time adaptations. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 24144088
- Volume :
- 8
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Multimodal Technologies & Interaction
- Publication Type :
- Academic Journal
- Accession number :
- 176903319
- Full Text :
- https://doi.org/10.3390/mti8040026