Le site de vulgarisation scientifique de l’Université de Liège. ULg, Université de Liège

Artificial intelligence and video games
3/16/15

Over the last ten years, the realism of the games has improved considerably to the point where graphic performances have reached the point where players are immersed in a quasi-real world, but the performances of AI systems have not followed suit. This has led to a dichotomy.  From the point of view of graphics, there is a similarity between reality and games; from the point of view of intelligence, there is a big difference with reality. “As graphics become more and more convincing, the difference has become increasingly marked: a very real form which does not at all act in a realistic way”! There is therefore some incoherence between the visual level and the level of AI of the different characters. In order to set themselves apart from their competitors, the actors in the sector have to “pull out all the stops” with regard to the development of much more efficient AI.

Gran turismoIn fact, in a racing game, for example, the computer does not really drive the vehicle the same way the player does; it simply guides the car by means of a series of possibilities and restrictions without knowing whether these are valid or necessary. Rather than worrying about whether the vehicle accelerates or decelerates with correct, plausible values, it cheats in order not to be beaten by the player. “We therefore have the impression that the computer cheats, does not play by the same rules as ours”, continues Damien Ernst. “To prevent this, the computer, has to consider the car as another player and use an AI algorithm to drive it, an algorithm capable of taking the same decisions as the human player”. If the AI of video games is of insufficient quality, this is because in competitive situations where a human being is pitted against a computer, the human is much better than the machine. This affirmation may seem strange if we remember, for example, the victories recorded by computers over the best chess players. “In cases like those”, explains Raphael Fonteneau, a researcher at the FNRS, “AI systems have sometimes succeeded in solving the game completely (without cheating!), but only in very structured, narrow environments where the rules can be defined precisely and are not so numerous: in addition, the solution to the game is based on the memorization of possibilities. But the computer is poor at appreciating a rich environment and this is what needs to be improved upon”.

Common basis

The work of the researchers from Liège and in particular that of Firas Safadi, including that which constitutes the core of his doctoral thesis, has attempted to get a grasp of the generic needs of AI developers for video games. Though game developers would certainly appreciate not having to build and AI from scratch for each game, they often find themselves forced to. However, while different AI solutions can give the impression of being different, they have in reality very similar requirements. The researchers from Liège have therefore considered that it was possible to create a generic AI system to which an adaptation layer could be added, making a connection between the specific needs of each video game. Firas Safadi worked on this transition layer between the two (middleware), between a generic AI and games. Thanks to his developments, it will no longer be necessary to design AI specific to each game (which is impossible, and it is this fact that affects the quality of current games). On the contrary, game designers will be able to use a generic AI and apply it to a large range of games.

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