A first endeavor for optimizing player satisfaction in augmented-reality games through the 'Playware' physical interactive platform is presented in this paper. Constructed user models, reported in the literature, map individual playing characteristics to reported entertainment preferences of augmented-reality game players. An adaptive mechanism then adjusts controllable game parameters in real-time in order to improve the entertainment value of the game for the player. The basic approach presented here applies gradient ascent to such a model to reveal the direction toward games of higher entertainment value while a rule-based system exploits the derivative information to adjust specific game parameters to augment the entertainment value. Those adjustments take place frequently during the game in small time intervals that maintain the constructed model's accuracy. Performance of the adaptation mechanism is evaluated using a game survey experiment. Results reveal that children show a notable preference for the adaptive versus the static Bug-Smasher ('Playware' test-bed) game variant even when simple adaptive approaches like the one proposed are used. The limitations and the use of the methodology as a baseline effective adaptive mechanism to entertainment augmentation are discussed.
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