Using Genetically Optimized Artificial Intelligence to improve Gameplaying Fun for Strategical Games

Fun in computer games depends on many factors. While some factors like uniqueness and humor can only be measured by human subjects, in a strategical game, the rule system is an important and measurable factor. Classics like chess and GO have a millennia-old story of success, based on clever rule design. They only have a few rules, are relatively easy to understand, but still they have myriads of possibilities. Testing the deepness of a rule-set is very hard, especially for a rule system as complex as in a classic strategic computer game. It is necessary, though, to ensure prolonged gaming fun. In our approach, we use artificial intelligence (Al) to simulate hours of beta-testing the given rules, tweaking the rules to provide more game-playing fun and deepness. To avoid making the Al a mirror of its programmer's gaming preferences, we not only evolved the At with a genetic algorithm, but also used three fundamentally different At paradigms to find boring loopholes, inefficient game mechanisms and, last but not least, complex erroneous behavior.