@inbook{0571bbfdc9be48cc8db4d26eef17cce7,
title = "Humans vs AI: An Exploratory Study with Online and Offline Learners",
abstract = "We present an exploratory study comparing human player performance against online and offline AI learning techniques—the Naive Bayes Classifier and Genetic Algorithms, respectively—using a simple turn-based game. Human player performance is also assessed according to gender, age, experience playing games, and boredom level during game sessions. Human players and AI techniques are shown to obtain statistically equivalent score distributions. No gender performance differences were found, although performance seems to decrease with age. To a lesser extent, performance appears to improve with self-assessed experience and boredom levels. This study offers a base for more comprehensive experiments, suggesting various directions for future research.",
keywords = "Computer games, Genetic Algorithms, Naive Bayes Classifier",
author = "Jo{\~a}o In{\'a}cio and Nuno Fachada and Matos-Carvalho, {Jo{\~a}o P.} and Fernandes, {Carlos M.}",
note = "Publisher Copyright: {\textcopyright} 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 13th International Conference on Videogame Sciences and Arts, VJ 2023 ; Conference date: 28-11-2023 Through 30-11-2023",
year = "2024",
month = jan,
day = "1",
doi = "10.1007/978-3-031-51452-4_19",
language = "English",
isbn = "9783031514517",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "272--286",
editor = "{Vale Costa}, Liliana and Nelson Zagalo and Veloso, {Ana Isabel} and M{\'a}rio Vairinhos and Diogo Gomes and Esteban Clua and Sylvester Arnab",
booktitle = "Videogame Sciences and Arts - 13th International Conference, VJ 2023, Revised Selected Papers",
address = "Germany",
}