The Role of Machine Learning in Game Development Domain - A Review of Current Trends and Future Directions

被引:2
|
作者
Edwards, Gemma [1 ]
Subianto, Nicholas [1 ]
Englund, David [1 ]
Goh, Jun Wei [1 ]
Coughran, Nathan [1 ]
Milton, Zachary [1 ]
Mirnateghi, Nima [1 ]
Shah, Syed Afaq Ali [1 ,2 ]
机构
[1] Murdoch Univ, Discipline Informat Technol, Murdoch, WA, Australia
[2] Edith Cowan Univ, Sch Sci, Perth, WA, Australia
关键词
Machine Learning; Artificial Intelligence; Video Games; Adaptive NPCs; Game Development; ARTIFICIAL-INTELLIGENCE; AI; FRAMEWORK; AGENTS;
D O I
10.1109/DICTA52665.2021.9647261
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Machine Learning is a relatively new and emergent field in video game development domain. Despite considerable relevance to the video game industry, there has yet to be a significant commercial product utilising machine learning in its design or function. Although previous research has shown significant potential in the use of video games in developing and testing Artificial Intelligence, the reverse i.e., using Artificial Intelligence to develop and test video games is far less common. This paper provides a survey of existing techniques and reviews current and future applications of machine learning in the field of video game development, both as a tool to streamline development and management processes and as an integrated part of video game end products themselves. This paper also explores a number of machine learning technologies not yet applied to use in the video game field and discusses their potential in future research and product development. Despite the relative newness and lack of development in this field, this paper finds that there is potential for machine learning to significantly improve and expedite production in the video game industry. Machine Learning can potentially be harnessed to develop new or improved products or automate development processes in conventional video game products.
引用
收藏
页码:495 / 501
页数:7
相关论文
共 50 条
  • [1] Machine Learning in Malware Analysis: Current Trends and Future Directions
    Altaha, Safa
    Riad, Khaled
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2024, 15 (01) : 1267 - 1279
  • [2] A systematic review of machine learning in logistics and supply chain management: current trends and future directions
    Akbari, Mohammadreza
    Do, Thu Nguyen Anh
    BENCHMARKING-AN INTERNATIONAL JOURNAL, 2021, 28 (10) : 2977 - 3005
  • [3] Machine learning applications in the diagnosis of leukemia: Current trends and future directions
    Salah, Haneen T.
    Muhsen, Ibrahim N.
    Salama, Mohamed E.
    Owaidah, Tarek
    Hashmi, Shahrukh K.
    INTERNATIONAL JOURNAL OF LABORATORY HEMATOLOGY, 2019, 41 (06) : 717 - 725
  • [4] Machine Learning in Pediatric Healthcare: Current Trends, Challenges, and Future Directions
    Ganatra, Hammad A.
    JOURNAL OF CLINICAL MEDICINE, 2025, 14 (03)
  • [5] Advancing legume quality assessment through machine learning: Current trends and future directions
    Rashvand, Mahdi
    Nikzadfar, Mehrad
    Laveglia, Sabina
    Mirmohammadrezaei, Hedie
    Bozorgi, Ahmad
    Paterna, Giuliana
    Matera, Attilio
    Gioia, Tania
    Altieri, Giuseppe
    Di Renzo, Giovanni Carlo
    Genovese, Francesco
    JOURNAL OF FOOD COMPOSITION AND ANALYSIS, 2025, 142
  • [6] Machine learning and orthodontics, current trends and the future opportunities: A scoping review
    Mohammad-Rahimi, Hossein
    Nadimi, Mohadeseh
    Rohban, Mohammad Hossein
    Shamsoddin, Erfan
    Lee, Victor Y.
    Motamedian, Saeed Reza
    AMERICAN JOURNAL OF ORTHODONTICS AND DENTOFACIAL ORTHOPEDICS, 2021, 160 (02) : 170 - +
  • [7] A review of machine learning methods for drought hazard monitoring and forecasting: Current research trends, challenges, and future research directions
    Prodhan, Foyez Ahmed
    Zhang, Jiahua
    Hasan, Shaikh Shamim
    Sharma, Til Prasad Pangali
    Mohana, Hasiba Pervin
    ENVIRONMENTAL MODELLING & SOFTWARE, 2022, 149
  • [8] A review of dialogue systems: current trends and future directions
    Atheer Algherairy
    Moataz Ahmed
    Neural Computing and Applications, 2024, 36 : 6325 - 6351
  • [9] A review of dialogue systems: current trends and future directions
    Algherairy, Atheer
    Ahmed, Moataz
    NEURAL COMPUTING & APPLICATIONS, 2023, 36 (12): : 6325 - 6351
  • [10] Current Trends in SLA Research and Directions for Future Development
    Long, Michael H.
    CHINESE JOURNAL OF APPLIED LINGUISTICS, 2012, 35 (02) : 135 - 152