@inproceedings{3ad1605a4d3547ac8d9d48f578e3a3d7,
title = "Modeling Individual Tacit Coordination Abilities",
abstract = "Previous experiments in tacit coordination games hinted that some people are more successful in achieving coordination than others, although the variability in this ability has not yet been examined before. With that in mind, the overarching aim of our study is to model and describe the variability in human decision-making behavior in the context of tacit coordination games. To do so we first conducted a large-scale experiment to collect behavioral data, modeled the decision-making behavior, and characterize their observed variability. We then used the proposed model by predicting the individual coordination ability of a player based on its constructed strategic profile model and demonstrated that there is a direct and significant relationship between the player{\textquoteright}s model and its coordination ability. Understanding the differences in individual{\textquoteright}s tacit coordination abilities as well as their unique strategic profiles will allow us to better predict human{\textquoteright}s behavior in tacit coordination scenarios and consequently construct better algorithms for human-machine interactions.",
keywords = "Cognitive modeling, Decision making, Tacit coordination games",
author = "Dor Mizrahi and Ilan Laufer and Inon Zuckerman",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 12th International Conference on Brain Informatics, BI 2019 ; Conference date: 13-12-2019 Through 15-12-2019",
year = "2019",
doi = "10.1007/978-3-030-37078-7_4",
language = "الإنجليزيّة",
isbn = "9783030370770",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "29--38",
editor = "Peipeng Liang and Vinod Goel and Chunlei Shan",
booktitle = "Brain Informatics - 12th International Conference, BI 2019, Proceedings",
}