Humans vs AI: An Exploratory Study with Online and Offline Learners

João Inácio, Nuno Fachada, João P. Matos-Carvalho, Carlos M. Fernandes

Research output: Chapter in Book/Report/Conference proceedingChapter

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.

Original languageEnglish
Title of host publicationVideogame Sciences and Arts - 13th International Conference, VJ 2023, Revised Selected Papers
EditorsLiliana Vale Costa, Nelson Zagalo, Ana Isabel Veloso, Mário Vairinhos, Diogo Gomes, Esteban Clua, Sylvester Arnab
PublisherSpringer Science and Business Media Deutschland GmbH
Pages272-286
Number of pages15
ISBN (Print)9783031514517
DOIs
Publication statusPublished - 1 Jan 2024
Event13th International Conference on Videogame Sciences and Arts, VJ 2023 - Aveiro, Portugal
Duration: 28 Nov 202330 Nov 2023

Publication series

NameCommunications in Computer and Information Science
Volume1984
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference13th International Conference on Videogame Sciences and Arts, VJ 2023
Country/TerritoryPortugal
CityAveiro
Period28/11/2330/11/23

Keywords

  • Computer games
  • Genetic Algorithms
  • Naive Bayes Classifier

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