Getting Started with Machine Learning in Game Development

Abstract

The The webinar and workshop titled "Getting Started with Machine Learning in Game Development", held on January 18, 2025, aimed to deliver foundational knowledge on Machine Learning (ML), with a specialized focus on Reinforcement Learning (RL) and its applications in game development, featuring two main sessions: a public webinar for theoretical education and a hands-on technical workshop. The webinar introduced core ML concepts, including Supervised Learning, Unsupervised Learning, and Reinforcement Learning, while the workshop emphasized the practical implementation of RL using Unity ML-Agents, PyTorch, Anaconda, and the C# programming language, attracting 45–56 participants from diverse institutions and highlighting significant interest in ML applications within the creative industry, particularly game development. Pre-test results (administered prior to the sessions) yielded an average score of 64.68 and a median of 60, while post-test scores (conducted after the sessions) showed marked improvement, with an average of 81.22 and a median of 90, and participant feedback was overwhelmingly positive, with attendees expressing satisfaction regarding the quality of content, expertise of speakers, and overall event organization, underscoring the effective reception of Machine Learning education and its potential to enhance skill development across sectors, including the creative and technology industries.

Webinar dan Workshop "Getting Started with Machine Learning in Game Development", yang diselenggarakan pada 18 Januari 2025, bertujuan memberikan pengetahuan dasar tentang Machine Learning (ML) dengan fokus khusus pada Reinforcement Learning (RL) dan penerapannya dalam pengembangan game. Acara terdiri dari dua sesi utama: edukasi publik melalui webinar dan pelatihan teknis melalui Workshop. Webinar membahas dasar-dasar Machine Learning, Supervised Learning, Unsupervised Learning, dan Reinforcement Learning, sementara Workshop berfokus pada penerapan RL menggunakan Unity ML-Agents, PyTorch, dan Anaconda dengan bahasa pemrograman C#. Acara ini berhasil menarik 45–56 peserta dari berbagai institusi, menunjukkan minat besar terhadap penerapan Machine Learning di industri kreatif, khususnya pengembangan game. Hasil dari Pre-test yang di mana peserta mengerjakan tes tersebut sebelum pemaparan materi memiliki nilai rata rata sebanyak 64,68 poin dan median sebanyak 60 poin, sedangkan di Post-Test, yang di mana peserta mengerjakan tes tersebut setelah mendengarkan paparan materi yang diberikan, memiliki rata-rata sebanyak 81,22 poin dan median sebanyak 90 poin. Selain itu, mayoritas peserta memberikan umpan balik positif, menyatakan kepuasan terhadap kualitas materi, narasumber, dan penyelenggaraan acara. Kegiatan ini menegaskan bahwa edukasi teknologi Machine Learning diterima dengan baik dan berpotensi mendukung pengembangan keterampilan di berbagai sektor, termasuk industri kreatif dan teknologi.