Finding a way to automate level creation, at least in part, is a significant achievement. And because this is so expensive, many of them are looking for effective ways to automate the process or assist the game designer. Game makers rely on human expertise and extensive testing to create good levels. But content creation is one of the most time-consuming and expensive parts of the development process. “Levels are of paramount importance, especially in first person shooter and platform games, as they greatly affect the player experience,” says Gicomello and co. Nevertheless, even this level of automation could have significant implications for game designers. For example, deep-learning networks struggle to produce fine detail, probably because of noisy data that is inevitably generated with this kind of approach. You can watch one of the levels being played here. The researchers have tested the new levels and say they are interesting to explore and play, with typical Doom features such as narrow tunnels and large rooms. “Our results show that generative adversarial networks can capture intrinsic structure of DOOM levels and appears to be a promising approach to level generation in first person shooter games,” say Giacomello and co. After some 36,000 iterations, the deep-learning networks were able to produce levels of good quality. The results show just how powerful this technique is. Then they used a deep-learning technique called a generative adversarial network to study the data and learn how to generate new levels. They also created a vector that captured important features of the level in numerical form, such as the size, area, and perimeter of rooms, the number of rooms, and so on. The team then processed each level to generate a set of images that represent its most important features, such as the walkable area, walls, floor height, objects, and so on. They begin with 1,000 Doom levels taken from a repository of publicly available games, which includes all the official levels from Doom and Doom 2 as well as more than 9,000 levels created by the gaming community. The team’s approach is relatively straightforward. These guys say it is indeed possible to create compelling Doom levels in this automated way, and that the technique has significant potential to change the way game content is created. Today we get an answer thanks to the work of Edoardo Giacomello and colleagues at the Politecnico di Milano in Italy. Is it possible to use this data to train a deep-learning algorithm to create its own levels of Doom that a human would find compelling? Indeed, large numbers of Doom levels-both official and player-created-are now freely available online, forming a formidable corpus for study and research.Īnd that raises an interesting possibility. The game is notable because it pioneered 3-D graphics for PCs running MS-DOS, introduced networked multiplay, and even allowed players to create their own game levels. The game is a first-person shooter in which a space marine battles to survive against various demons and zombies. One of the longest-lasting and most successful video-game franchises is the Doom series, launched in 1993 and still going strong with over 10 million copies sold.
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