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Automatic content generation can have a significant role in adaptivity in games. Research in this field has presented results that encourage a focus on customized content generation, the automatic creation of virtual worlds to better suit individual players.

Previous work in automatic content generation has traditionally relied on procedural methods and has succeeded in creating realistic game environments. For at least thirty years, many different procedures have been proposed to automatically create such content as terrain, tree and plant models and urban environments. Results show that a common shortcoming in traditional procedural methods is the lack of control over the generated output, due to the randomness that these algorithms carry. Therefore, researchers are now aiming at more controllable procedural methods, allowing designers to steer content generation.

Work developed by Muller, Parberry and many more, on controllable content generation, is enabling procedural methods to become more flexible and accurate. While maintaining its automatic nature, these methods are allowing game designers to steer automatic content generation by means of a better expression of their intent. However, control over the generated output only relates to defining physical properties for the desired environments.

These results encourage further work on using controllable content generation to adapt game environments. To do so, the challenge ahead becomes twofold: (i) controlling content generation by using knowledge about all sorts of high-level targets (game goals, player expectations, qualitative features), and (ii) ensuring that this knowledge is generic and applicable to each player. Solving these problems will make it possible to create customized content, in the sense that game environments would be generated before game time, according to knowledge about individual players. This knowledge should go beyond player preferences (e.g. favorite colors) and focus on what affects his playing motivations or purposes. As an example, consider a world domination strategy game and a player who aims to be an economic leader and use trade strategies. A matching virtual world for this could be generated so that, for example, the player homeland is located close to natural resources, in an intermediate position between opponent cities, and has a flat and oceanic geography (that allows the fast development of travel strategies).

Current research is already tackling some of the challenges identified above, and its methods could be valuable to future work in customized content creation. Semantic and declarative modeling techniques are already capable of controlling procedural methods by embedding knowledge in virtual objects. This encourages further research on customized content generation through semantic techniques. By developing such semantic schemes, further specifications can be used to embed meaning about player purposes in the virtual world and its objects. This meaning could be used to control the generation of customized content.


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