Automatic computer game balancing: a reinforcement learning approach
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Presence: Teleoperators and Virtual Environments - Special issue: Virtual heritage
Flow in games (and everything else)
Communications of the ACM
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Using coevolution to understand and validate game balance in continuous games
Proceedings of the 10th annual conference on Genetic and evolutionary computation
O' game, can you feel my frustration?: improving user's gaming experience via stresscam
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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In this paper, we present a novel methodology to improve gaming experiences by automatically adjusting the game difficulty throughout the game play using a Profile-based Adaptive Difficulty System (PADS). We utilize a player's gaming experience and objective to create a player profile. Utilizing this profile and a performance-based algorithm, the PADS customizes the game's difficulty levels to accommodate each individual. Our experimental results successfully demonstrate improvements in both perceptual and actual gaming experiences. With our approach, traditional program-centered video games can be transformed to provide individualized, player-centered gaming experiences.