This study deals with the problems of aggregating the opinions of a group of people in such a way that the quality of the group decision surpasses the quality of the decision of the most experienced individual within the group. The methods we have studied fall in the research domain of the so called collective intelligence. We provide an overview of the state-of-the-art in the collective intelligence. We describe the method based on adaptive boosting we have proposed aggregatig the opinions of a group of people. We have implemented a web application to gather opinions of people and used the application to collect data for the experimental analysis. The model problem was to identify whether there is or there is not a tumor present in the series of X-ray images of human lungs. We have compared our proposed method to conventional methods such as majority voting. We have concluded that our proposed method can be successfully used to aggregate opinions of a group of people to increase their collective intelligence above the level of the most successful individual within the group in many cases. We have observed that the highest increase in the collective intelligence may be achieved for intelligence wise homogeneous groups what confirms the results of previous studies.
Publié le : 2017-02-13
Classification:
Knowledge and Information Engineering,
Collective intelligence, modified adaptive boosting, aggregation break of opinions,
68T05
@article{cai3669,
author = {Marek Bundzel; Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Ko\v sice and Jozef Lacko; Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Ko\v sice and Iveta Zolotov\'a; Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Ko\v sice and Tom\'a\v s Kasanick\'y; Institute of Informatics, Slovak Academy of Sciences, Bratislava and J\'an Zelenka; Institute of Informatics, Slovak Academy of Sciences, Bratislava},
title = {Artificial Intelligence Aggregating Opinions of a Group of People},
journal = {Computing and Informatics},
volume = {35},
number = {4},
year = {2017},
language = {en},
url = {http://dml.mathdoc.fr/item/cai3669}
}
Marek Bundzel; Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice; Jozef Lacko; Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice; Iveta Zolotová; Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice; Tomáš Kasanický; Institute of Informatics, Slovak Academy of Sciences, Bratislava; Ján Zelenka; Institute of Informatics, Slovak Academy of Sciences, Bratislava. Artificial Intelligence Aggregating Opinions of a Group of People. Computing and Informatics, Tome 35 (2017) no. 4, . http://gdmltest.u-ga.fr/item/cai3669/