56 citations · 85 across the 7 of their papers we have counts for
7 papers
Amortised Design Optimization for Item Response Theory
Antti Keurulainen, Isak Westerlund, Oskar Keurulainen +1
Item Response Theory (IRT) is a well known method for assessing responses from humans in education and psychology. In education, IRT is used to infer student abilities and characte…
Amortised Experimental Design and Parameter Estimation for User Models of Pointing
Antti Keurulainen, Isak Westerlund, Oskar Keurulainen +1
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 data.…
Online simulator-based experimental design for cognitive model selection
Alexander Aushev, Aini Putkonen, Gregoire Clarte +4
The problem of model selection with a limited number of experimental trials has received considerable attention in cognitive science, where the role of experiments is to discrimina…
Rediscovering Affordance: A Reinforcement Learning Perspective
Yi-Chi Liao, Kashyap Todi, Aditya Acharya +3
Affordance refers to the perception of possible actions allowed by an object. Despite its relevance to human-computer interaction, no existing theory explains the mechanisms that u…
Likelihood-Free Inference in State-Space Models with Unknown Dynamics
Alexander Aushev, Thong Tran, Henri Pesonen +2
Likelihood-free inference (LFI) has been successfully applied to state-space models, where the likelihood of observations is not available but synthetic observations generated by a…
Implications of Human Irrationality for Reinforcement Learning
Haiyang Chen, Hyung Jin Chang, Andrew Howes
Recent work in the behavioural sciences has begun to overturn the long-held belief that human decision making is irrational, suboptimal and subject to biases. This turn to the rati…
Inferring Cognitive Models from Data using Approximate Bayesian Computation
Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes +3
An important problem for HCI researchers is to estimate the parameter values of a cognitive model from behavioral data. This is a difficult problem, because of the substantial comp…