Preverjanje veljavnosti realno-časovnega igralnega prostora z algoritmom razširjenega sistema na osnovi klasifikatorjev : doktorska disertacija

slovenian

doktorska dela

2021

extended classifier system   game feature validation   game space   playtesting agent   real-time strategy game

Univerza v Mariboru, Fakulteta za elektrotehniko računalništvo in informatiko

With our doctoral dissertation, we address the topic of time-consuming manual validation of real-time game spaces. Current modern gaming spaces are incredibly complex systems and comprise of many game features representing the game's characteristics. That complexity makes it hard to validate the game features with human players because repetitive operations during replay of the pre-planned game scenarios can lead to the unintentional introduction of errors in the validation process. Human testing is an expensive and elaborate process, so during the doctoral thesis, we automated this process with an eXtended Classifier System (XCS) algorithm. The algorithm XCS was used to create a game agent that works independently in any real-time game space. Then we developed a non-invasive component that allows the adaptation of any game agent into a game-testing agent. We designed the first experiment to confirm the concept that using a non-invasive component, our game agent with algorithm XCS could detect invalid game features in the lowest representative of real-time game spaces (game space of Tic-Tac-Toe). We developed the metric to compare our agent with other game-testing agents by utilizing quantitative metric scores. The game space, game functionalities, game scenarios, game agents, non-invasive component, and metric were combined into the method for quantitative assessment of the game space's validity. The method was evaluated in the second experiment, in which our agent was compared against other state-of-the-art game agents in the highest representative of real-time game spaces (real-time strategy games). In both experiments, measurements of the successful confirmations of invalid game features were taken for all game test agents. Additionally, we took time measurements of the execution of an individual game scenario for the game-agent with algorithm XCS. Both experiments revealed that the XCS algorithm is suitable for the validation of game features because it detected invalid game features every time they did not work correctly. In the second experiment, we also showed that whenever other game-testing agents discovered the invalid game features, so did our game-testing agent. By comparing our agent's final metric scores against metric scores of other game-testing agents, we concluded that it is comparable to them and ranks in the middle. Through a review of the time measurements, we discovered that they could vary statistically during the repetition of the same scenarios. Still, nonetheless, all scenarios were executed within the predicted limits of the set real-time values. The XCS algorithm has proven to be a worthy candidate to verify real-time game spaces' game features.

07.08.2023