  With breakthrough of the AlphaGo, human-computer gaming AI has ushered in a
big explosion, attracting more and more researchers all around the world. As a
recognized standard for testing artificial intelligence, various human-computer
gaming AI systems (AIs) have been developed such as the Libratus, OpenAI Five
and AlphaStar, beating professional human players. The rapid development of
human-computer gaming AIs indicate a big step of decision making intelligence,
and it seems that current techniques can handle very complex human-computer
games. So, one natural question raises: 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 gaming; 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 this brief review
can provide an introduction for beginners, and inspire insights for researchers
in the field of AI in human-computer gaming.
