Percorrer por autor "Barreiros, Filipa F."

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    Active learning prototypes for teaching game AI
    (IEEE Computer Society, 2023) Fachada, Nuno; Barreiros, Filipa F.; Lopes, Phil; Fonseca, Micaela; COPELABS (FCT) - Centro de Investigação em Computação Centrada nas Pessoas e Cognição (CTS); HEI-LAB (FCT) - Digital Laboratories for Environments and Human Interactions
    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.