Towards Optimizing Human-Centric Objectives in AI-Assisted Decision-Making With Offline Reinforcement Learning
As AI assistance is increasingly infused into decision-making processes, we may seek to
optimize human-centric objectives beyond decision accuracy, such as skill improvement or …
optimize human-centric objectives beyond decision accuracy, such as skill improvement or …
CRTypist: Simulating Touchscreen Typing Behavior via Computational Rationality
Touchscreen typing requires coordinating the fingers and visual attention for button-
pressing, proofreading, and error correction. Computational models need to account for the …
pressing, proofreading, and error correction. Computational models need to account for the …
Explaining crowdworker behaviour through computational rationality
MA Hedderich, A Oulasvirta - Behaviour & Information Technology, 2024 - Taylor & Francis
Crowdsourcing has transformed whole industries by enabling the collection of human input
at scale. Attracting high quality responses remains a challenge, however. Several factors …
at scale. Attracting high quality responses remains a challenge, however. Several factors …
Heads-Up Multitasker: Simulating Attention Switching On Optical Head-Mounted Displays
Optical Head-Mounted Displays (OHMDs) allow users to read digital content while walking.
A better understanding of how users allocate attention between these two tasks is crucial for …
A better understanding of how users allocate attention between these two tasks is crucial for …
Mobile User Interface Adaptation Based on Usability Reward Model and Multi-Agent Reinforcement Learning
D Vidmanov, A Alfimtsev - Multimodal Technologies and Interaction, 2024 - mdpi.com
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 …
the tasks of automatically adapting computer systems to user needs. However, implementing …
Enabling Uniform Computer Interaction Experience for Blind Users through Large Language Models
Blind individuals, who by necessity depend on screen readers to interact with computers,
face considerable challenges in navigating the diverse and complex graphical user …
face considerable challenges in navigating the diverse and complex graphical user …
Pedestrian crossing decisions can be explained by bounded optimal decision-making under noisy visual perception
Y Wang, AR Srinivasan, JPP Jokinen… - arXiv preprint arXiv …, 2024 - arxiv.org
This paper presents a model of pedestrian crossing decisions, based on the theory of
computational rationality. It is assumed that crossing decisions are boundedly optimal, with …
computational rationality. It is assumed that crossing decisions are boundedly optimal, with …
Understanding the Effects of Visual Impairment on Visual Search
D Aljasem, A Howes - International Conference on Human-Computer …, 2024 - Springer
The effect of vision loss on visual search has been extensively studied in psychology, but
little is known about the relevance of these insights to human-computer interaction (HCI) …
little is known about the relevance of these insights to human-computer interaction (HCI) …
[PDF][PDF] Mobile User Interface Adaptation Based on Usability Reward Model and Multi-Agent Reinforcement Learning. Multimodal Technol. Interact. 2024, 8, 26
D Vidmanov, A Alfimtsev - 2024 - researchgate.net
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 …
the tasks of automatically adapting computer systems to user needs. However, implementing …