Beskrivelse
Evolutionary computation techniques have proven to be a valuable instrument for adaptation and content generation in computer games, allowing to automatically generate high quality content tailored to specific requirements. The adaptation of weapons in Galactic Arms Race and the generation of Super Mario Bros levels are two successful examples of the application of such techniques to game content generation.In these examples, as in many others, evolutionary computation is used to find an optimal configuration of a set of game parameters to optimize a number of game experience predictors/heuristics. When applying evolutionary computation techniques in such contexts, a common problem to face is the uncertainty of the objective function under optimization. Such uncertainty may be due to several reasons: there is uncertainty in the evaluation (e.g. if the function depends on real-time sensor data), the objective function depends on dynamic game elements (e.g. in automatic camera control), or the objective function depends on player preferences which are stochastic by nature and might evolve over time.
In this tutorial, I will cover state-of-the-art methods to deal with uncertainty in optimization. Different game adaptation scenarios and objective functions will be covered as examples, ranging from dynamic and realtime optimization to off-line content generation.
| Periode | 11 sep. 2012 |
|---|---|
| Begivenhedstitel | IEEE Conference on Computational Intelligence And Games |
| Begivenhedstype | Konference |
| Placering | Granada, SpanienVis på kort |