Active learning prototypes for teaching game AI

Miniatura indisponível

Data

2023

Título da revista

ISSN da revista

Título do Volume

Editora

IEEE Computer Society
5th Annual IEEE Conference on Games, CoG 2023

Resumo

Artificial intelligence (AI) in computer games can enhance the player experience by providing more realistic and dynamic interactions with non-player characters and/or the game environment and is, therefore, an essential skill for game development students to acquire. In this paper, we discuss ten active learning prototypes for undergraduate game development students focusing on AI for Games. The prototypes were implemented in the Unity game engine, and each prototype considers a particular technique or set of algorithms. Depending on the prototype, students are required to interact with it on two levels: 1) by running it within the Unity editor, manipulating the respective technique's parameters, and experimenting and/or playing with the implemented demo or game; or, 2) in addition to the previous level, by actively changing and expanding the provided code to achieve the desired behavior or result. We performed a survey immediately after contact with the prototypes and found that they were easy for the students to manipulate and/or build upon, and most significantly, that they helped students understand the associated techniques and algorithms.

Descrição

Publisher Copyright: © 2023 IEEE.

Palavras-chave

EDUCAÇÃO, JOGOS DE COMPUTADOR, DESENVOLVIMENTO DE JOGOS DE COMPUTADOR, APRENDIZAGEM, INTELIGÊNCIA ARTIFICIAL, VIDEOJOGOS, INFORMÁTICA, EDUCATION, COMPUTER GAMES, COMPUTER GAMES DEVELOPMENT, LEARNING, ARTIFICIAL INTELLIGENCE, VIDEOGAMES, COMPUTER SCIENCE

Citação

Fachada, N, Barreiros, F F, Lopes, P & Fonseca, M 2023, Active learning prototypes for teaching game AI. in Proceedings of the 2023 IEEE Conference on Games, CoG 2023. IEEE Conference on Computatonal Intelligence and Games, CIG, IEEE Computer Society, 5th Annual IEEE Conference on Games, CoG 2023, Boston, United States, 21/08/23. https://doi.org/10.1109/CoG57401.2023.10333229

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