This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. Since the inception of artificial intelligence in the 1950s, we've been trying to find ways to measure progress in the field of AI. For many, the golden criteria for AI the Turing Test, an evaluation of whether a computer can exhibit human behavior. But the Turing Test only defines whether AI can fool humans, not compete with them, and it's very hard to say how deep the Test goes. A much better arena to test the extent of AI's intelligence, many scientists believe, are games, domains where contestants can measure and compare their success and clearly determine which one performs better.
Artificial Intelligence (AI) has become one of the most trending buzzwords in gaming industry of today. Almost every game developer now strives to add some flavor of AI in their video games to generate responsive, adaptive and intelligent behaviors that mimic human cognition. AI in video games may sound as a new innovation, but one of the very first attempts to use game AI had been made in 1950s when Arthur Lee Samuel, an American pioneer in the field of computer gaming and AI, built a self-learning Checkers-playing program. AI has come a long way since then, from IBM's Deep Blue that defeated a reigning world chess champion, Garry Kasparov, on 11 May 1997 to Google's AlphaGo AI Go player that defeated the world's best human Go player. However, the future of AI in video games is not just to outsmart humans, but to generate a user experience that is better and more unique.
Did you miss a session from the Future of Work Summit? In 2019, San Francisco-based AI research lab OpenAI held a tournament to tout the prowess of OpenAI Five, a system designed to play the multiplayer battle arena game Dota 2. OpenAI Five defeated a team of professional players -- twice. And when made publicly available, OpenAI Five managed to win against 99.4% of people who played against it online. OpenAI has invested heavily in games for research, developing libraries like CoinRun and Neural MMO, a simulator that plops AI in the middle of an RPG-like world. But that approach is changing.
With breakthrough of AlphaGo, AI in human-computer game has become a very hot topic attracting researchers all around the world, which usually serves as an effective standard for testing artificial intelligence. Various game AI systems (AIs) have been developed such as Libratus, OpenAI Five and AlphaStar, beating professional human players. 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 for the intelligent decision making field ; 2) illustrate the mainstream frameworks and techniques for developing professional level AIs; 3) raise the challenges or drawbacks in the current AIs for intelligent decision making; and 4) try to propose future trends in the games and intelligent decision making techniques. Finally, we hope this brief review can provide an introduction for beginners, inspire insights for researchers in the filed of AI in games.
This paper reviews the field of Game AI, which not only deals with creating agents that can play a certain game, but also with areas as diverse as creating game content automatically, game analytics, or player modelling. While Game AI was for a long time not very well recognized by the larger scientific community, it has established itself as a research area for developing and testing the most advanced forms of AI algorithms and articles covering advances in mastering video games such as StarCraft 2 and Quake III appear in the most prestigious journals. Because of the growth of the field, a single review cannot cover it completely. Therefore, we put a focus on important recent developments, including that advances in Game AI are starting to be extended to areas outside of games, such as robotics or the synthesis of chemicals. In this article, we review the algorithms and methods that have paved the way for these breakthroughs, report on the other important areas of Game AI research, and also point out exciting directions for the future of Game AI.