Editorial: Applications of Artificial Intelligence and Machine Learning in Games

Recent developments in AI and machine learning technologies have significantly expanded their application area in games [1,2]. From more traditional tasks like creating AI-powered opponents, research has progressed to topics like gamification [3,4], AI-assisted content generation [5], and the use of large language models [6,7].

The present Special Issue shows the broadness of the current agenda of game-related AI studies. Six papers, forming this issue, represent the following domains:

Machine learning in education and gamification. Sánchez-Ruiz et al. [Contributions1] examined possible use scenarios and impacts of the large language model ChatGPT in a context of a university-level mathematics course. Swacha and Gracel [Contributions2] performed a systematic review of the research works dedicated to machine learning and gamification, reflecting on the historical developments as well as the current state of the field.

AI-assisted animation and asset generation. Lungu-Stan and Mocanu [Contributions3] explored the capabilities and challenges of deep-learning-powered character animation and asset generation. The authors also proposed their own solutions which are able to address some of the identified challenges.

Applications and evaluation of reinforcement learning technologies. Yu et al. [Contributions4] examined the use of reinforcement learning in wargames, with possible applications to real-life warfare scenarios. Guo et al. [Contributions5] extended the give-or-take social dilemma model to Markov games and designed a reinforcement-learning-based Admission algorithm which is able to learn the concepts of cooperation and equality. Mahajan et al. [Contributions6] evaluated the performance of various reinforcement learning-based methods in a Super Mario Bros.-like GAN-generated environment.

The diversity of topics and approaches pursued by these authors point towards the underexplored areas of machine learning in games and suggest some potential directions for further research efforts. We wish to thank all of the authors of the present Special Issue and encourage new contributions to gaming and AI technologies.

Conflicts of Interest

The authors declare no conflicts of interest.

List of Contributions

1. Sánchez-Ruiz, L.M.; Moll-López, S.; Nuñez-Pérez, A.; Moraño-Fernández, J.A.; Vega-Fleitas, E. ChatGPT Challenges Blended Learning Methodologies in Engineering Education: A Case Study in Mathematics. Appl. Sci. 2023, 13, 6039. https://doi.org/10.3390/app13106039.

2. Swacha, J.; Gracel, M. Machine Learning in Gamification and Gamification in Machine Learning: A Systematic Literature Mapping. Appl. Sci. 2023, 13, 11427. https://doi.org/10.3390/app132011427.

3. VLungu-Stan, C.; Mocanu, I.G. 3D Character Animation and Asset Generation Using Deep Learning. Appl. Sci. 2024, 14, 7234, https://doi.org/10.3390/app14167234.

4. Yu, S.; Zhu, W.; Wang, Y. Research on Wargame Decision-Making Method Based on Multi-Agent Deep Deterministic Policy Gradient. Appl. Sci. 2023, 13, 4569. https://doi.org/10.3390/app13074569.

5. Guo, T.; Yuan, Y.; Zhao, P. Admission-Based Reinforcement-Learning Algorithm in Sequential Social Dilemmas. Appl. Sci. 2023, 13, 1807. https://doi.org/10.3390/app13031807.

6. Mahajan, S.; Patil, S.; Bhavnagri, M.; Singh, R.; Kalra, K.; Saini, B.; Kotecha, K.; Saini, J. Performance Analysis of Reinforcement Learning Techniques for Augmented Experience Training Using Generative Adversarial Networks. Appl. Sci. 2022, 12, 12923. https://doi.org/10.3390/app122412923.

Footnotes

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References

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2. Xia, B.; Ye, X.; Abuassba, A.O. Recent research on ai in games. Proceedings of the 16th International Wireless Communications and Mobile Computing Conference, IWCMC 2020; Limassol, Cyprus, 15–19 June 2020; pp. 505-510.

3. Bennani, S.; Maalel, A.; Ghezala, H.B. Adaptive gamification in E-learning: A literature review and future challenges. Comput. Appl. Eng. Educ.; 2022; 30, pp. 628-642. [DOI: https://dx.doi.org/10.1002/cae.22477]

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6. Gallotta, R.; Todd, G.; Zammit, M.; Earle, S.; Liapis, A.; Togelius, J.; Yannakakis, G.N. Large Language Models and Games: A Survey and Roadmap. arXiv; 2024; arXiv: 2402.18659[DOI: https://dx.doi.org/10.1109/TG.2024.3461510]

7. Sweetser, P. Large Language Models and Video Games: A Preliminary Scoping Review. Proceedings of the CUI ’24: Proceedings of the 6th ACM Conference on Conversational User Interfaces; Luxembourg, 8–10 July2024; pp. 1-8. [DOI: https://dx.doi.org/10.1145/3640794.3665582]