Abstract
Machine learning is being deployed in games for adaptive content creation, adaptive difficulty levels, adaptive games, and intelligent NPC behavior. This comprehensive overview of machine learning game-oriented algorithms applied in applications introduces the reader to fundamental techniques-Decision Trees and Support Vector Machines-before introducing more advanced approaches: Deep Reinforcement Learning and Generative Adversarial Networks. We contrast the algorithms on high-level game challenges such as real-time decision-making, procedural content generation, and player modeling. We also outline the trade-offs between model complexity, computational efficiency, scalability, and player experience. Recent trends, challenges, and directions for future work are abstracted from large case studies and experimentally determined performance bounds. The book also identifies actionable recommendations for researchers and game developers looking to harness machine learning to create smarter, more adaptive, and more engaging gaming experiences.
References
- Nawalagatti, Amitvikram, and R. Kolhe Prakash. "A Comprehensive Review on Artificial Intelligence based Machine Learning Techniques for Designing Interactive Characters." International Journal of Mathematics and Computer Applications Research (IJMCAR) 8, no. 3 (2018): 1-10.
- Tabassum, Mujahid, Sundresan Perumal, Hadi Nabipour Afrouzi, Saad Bin Abdul Kashem, and Waqar Hassan. "Review on using Artificial Intelligence related Deep Tearning Techniques in Gaming and recent Networks." In Deep Learning in Gaming and Animations, CRC Press, 2021.
- Mekni, Mehdi, Charitha Sree Jayaramireddy, and Sree Veera Venkata Sai Saran Naraharisetti. "Reinforcement Learning Toolkits for Gaming: A Comparative Qualitative Analysis." Journal of Software Engineering and Applications 15, no. 12 (2022): 417-435.
- Hu, Zhipeng, Yu Ding, Runze Wu, Lincheng Li, Rongsheng Zhang, Yujing Hu, Feng Qiu et al. "Deep learning Applications in Games: A Survey from a Data Perspective." Applied Intelligence 53, no. 24 (2023): 31129-31164.
- Barman, Nabajeet, Emmanuel Jammeh, Seyed Ali Ghorashi, and Maria G. Martini. "No-Reference Video Quality Estimation based on Machine Learning for Passive Gaming Video Streaming Applications." IEEE Access 7 (2019): 74511-74527.
- Sarker, Iqbal H. "Machine learning: Algorithms, Real-World Applications and Research Directions." SN Computer Science 2, no. 3 (2021): 160.
- Zhao, Lei, and Jie Zhang. "Machine Learning based Business Intelligence Security and Privacy Analysis with Gaming Model in Training Complexity Application." Entertainment Computing 50 (2024): 100695.
- Gombolay, Matthew C., Reed E. Jensen, and Sung-Hyun Son. "Machine Learning Techniques for Analyzing Training Behavior in Serious Gaming." IEEE Transactions on Games 11, no. 2 (2017): 109-120.
- Usha, J., and Viji Vinod. "Video Gaming Therapy Analysis of Gaming Applications Using Reinforcement Learning." Journal of Data Acquisition and Processing 39, no. 1 (2024): 1278-1290.
- Diaz, Carlos Gonzalez, Phoenix Perry, and Rebecca Fiebrink. "Interactive Machine Learning for more Expressive Game Interactions." In 2019 IEEE Conference on Games (CoG), pp. 1-2. IEEE, 2019.
- Bowling, Michael, Johannes Fürnkranz, Thore Graepel, and Ron Musick. "Machine Learning and Games." Machine learning 63, no. 3 (2006): 211-215.
- Fürnkranz, Johannes. "Machine Learning and Game Playing." Springer. (2017): 783-788.
- Moriarty, Christopher Lawrence, and Avelino J. Gonzalez. "Learning Human Behavior from Observation for Gaming Applications." In FLAIRS. 2009.
- Rismayanti, Nurul. "Predicting Behaviour Using Machine Learning Techniques." Indonesian Journal of Data and Science 5, no. 2 (2024): 133-143.
- Samuel, Arthur L. "Some Studies in Machine Learning using the Game of Checkers. II—Recent Progress." IBM Journal of Research and Development 11, no. 6 (1967): 601-617.
- Edwards, Gemma, Nicholas Subianto, David Englund, Jun Wei Goh, Nathan Coughran, Zachary Milton, Nima Mirnateghi, and Syed Afaq Ali Shah. "The Role of Machine Learning in Game Development Domain-a Review of Current Trends and Future Directions." 2021 Digital Image Computing: Techniques and Applications (DICTA) (2021): 01-07.