@inproceedings{0592214ddbbb49679563649535d3aa4b,
title = "MAS4Games: A Reinforced Learning-Based Multi-agent System to Improve Player Retention in Virtual Reality Video Games",
abstract = "In this paper, we present a Q-learning-based multi-agent system designed for Dynamic Difficulty Adjustment (DDA) in a 3D fighting game. Our primary goal is to enhance the player{\textquoteright}s gaming experience through dynamic game difficulty adjustments based on their performance. We leverage the Unity game development platform and the ML-Agents framework to implement the Q-learning algorithm, training intelligent agents to adapt the game{\textquoteright}s difficulty. Our findings underscore the efficacy of Q-learning and multi-agent systems in improving DDA for video games. In the conclusion section, we discuss potential implications and future directions for our research.",
keywords = "Artificial intelligence, Difficulty level adaptation, Dynamic difficulty adjustment, Game development, Gaming experience, Intelligent agent Training, ML-agents framework, Multi-agent systems, Player performance, Q-learning, Unity 3D, Video games, Virtual reality",
author = "Natalia Maury-Casta{\~n}eda and Sergio Villarruel-Vasquez and Willy Ugarte",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 7th International Conference on Computer-Human Interaction Research and Applications, CHIRA 2023 ; Conference date: 16-11-2023 Through 17-11-2023",
year = "2023",
doi = "10.1007/978-3-031-49368-3\_7",
language = "Ingl{\'e}s",
isbn = "9783031493676",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "104--120",
editor = "\{da Silva\}, \{Hugo Pl{\'a}cido\} and \{da Silva\}, \{Hugo Pl{\'a}cido\} and Pietro Cipresso",
booktitle = "Computer-Human Interaction Research and Applications - 7th International Conference, CHIRA 2023, Proceedings",
}