Towards machines that understand people
The ability to estimate the state of a human partner is an insufficient basis on which to build
cooperative agents. Also needed is an ability to predict how people adapt their behavior in …
cooperative agents. Also needed is an ability to predict how people adapt their behavior in …
Designing optimal behavioral experiments using machine learning
Computational models are powerful tools for understanding human cognition and behavior.
They let us express our theories clearly and precisely and offer predictions that can be …
They let us express our theories clearly and precisely and offer predictions that can be …
Amortised experimental design and parameter estimation for user models of pointing
A Keurulainen, IR Westerlund, O Keurulainen… - Proceedings of the …, 2023 - dl.acm.org
User models play an important role in interaction design, supporting automation of
interaction design choices. In order to do so, model parameters must be estimated from user …
interaction design choices. In order to do so, model parameters must be estimated from user …
Real-time and sample-efficient learning of computationally rational user models
A Keurulainen - 2024 - aaltodoc.aalto.fi
To effectively collaborate with humans, Artificial Intelligence (AI) systems must understand
human behavior and the factors influencing it, including their goals, preferences, and …
human behavior and the factors influencing it, including their goals, preferences, and …
[PDF][PDF] Bayesian experimental design for implicit models using mutual information
S Kleinegesse - 2022 - core.ac.uk
Scientists regularly face the challenging task of designing experiments in such a way that
the collected data is informative and useful. The field of Bayesian experimental design …
the collected data is informative and useful. The field of Bayesian experimental design …