The Effects of Cognitive Biases and Imperfectness in Long-term Robot-Human Interactions: Case Studies using Five Cognitive Biases on Three Robots

The research presented in this paper demonstrates a model for aiding human-robot companionship based on the principle of 'human' cognitive biases applied to a robot. The aim of this work was to study how cognitive biases can affect human-robot companionship in long-time. In the current paper, we show comparative results of the experiments using five biased algorithms in three different robots such as ERWIN, MyKeepon and MARC. The results were analysed to determine what difference if any of biased vs unbiased interaction has on the interaction with the robot and if the participants were able to form any kind of 'preference' towards the different algorithms. The experimental presented show that the participants have more of a preference towards the biased algorithm interactions than the robot without the bias

The Effects of Cognitive Biases and Imperfectness in Long-term Robot-Human Interactions: Case Studies using Five Cognitive Biases on Three Robots.

Authors:

 M. Biswas    University of Lincoln, School of Computer Science, Lincoln, UK
J. Murray    University of Lincoln, School of Computer Science, Lincoln, UK

Published in:

· Journal

Cognitive Systems Research archive

Volume 43 Issue C, June 2017
Pages 266-290
Elsevier Science Publishers B. V. Amsterdam, The Netherlands, The Netherlands
table of contents doi>10.1016/j.cogsys.2016.07.007

Also Available from: https://www.researchgate.net/publication/306520502_The_Effects_of_Cognitive_Biases_and_Imperfectness_in_Long-term_Robot-Human_Interactions_Case_Studies_using_Five_Cognitive_Biases_on_Three_Robots [accessed Jul 8, 2017].