Player Dominance Adjustment Motion Gaming AI for Health Promotion

This paper presents an opponent fighting game AI for promoting balancedness in use of body segments of the player during full-body motion gaming. The proposed AI, named PDAHP-AI, is based on Monte Carlo tree-search and employs a recently purposed concept called Player Dominance Adjustment, where the AI determines its actions based on the player’s inputs so as to adjust the player’s dominant power. The basic idea is to let the player dominate the game when they perform healthy movement and on the contrary to have the AI take a strong action against the player when she or he performs unhealthy movement. The AI outperforms an existing dynamic difficulty adjustment AI designed for the same propose.