AI in Human-computer Gaming: Techniques, Challenges and Opportunities

• Published in: International journal of automation and computing 2023-06, Vol.20 (3), p.299-317
• Main Authors: Yin, Qi-Yue, Yang, Jun, Huang, Kai-Qi, Zhao, Mei-Jing, Ni, Wan-Cheng, Liang, Bin, Huang, Yan, Wu, Shu, Wang, Liang
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Card games; Computer & video games; Decision making; Questions; Trends
• ISSN: 2731-538X; 1476-8186; 2731-5398; 1751-8520
• DOI: 10.1007/s11633-022-1384-6

With the breakthrough of AlphaGo, human-computer gaming AI has ushered in a big explosion, attracting more and more researchers all over the world. As a recognized standard for testing artificial intelligence, various human-computer gaming AI systems (AIs) have been developed, such as Libratus, OpenAI Five, and AlphaStar, which beat professional human players. The rapid development of human-computer gaming AIs indicates a big step for decision-making intelligence, and it seems that current techniques can handle very complex human-computer games. So, one natural question arises: What are the possible challenges of current techniques in human-computer gaming and what are the future trends? To answer the above question, in this paper, we survey recent successful game AIs, covering board game AIs, card game AIs, first-person shooting game AIs, and real-time strategy game AIs. Through this survey, we 1) compare the main difficulties among different kinds of games and the corresponding techniques utilized for achieving professional human-level AIs; 2) summarize the mainstream frameworks and techniques that can be properly relied on for developing AIs for complex human-computer games; 3) raise the challenges or drawbacks of current techniques in the successful AIs; and 4) try to point out future trends in human-computer gaming AIs. Finally, we hope that this brief review can provide an introduction for beginners and inspire insight for researchers in the field of AI in human-computer gaming.