Towards adaptive motion gaming AI with player's behavior modeling for health promotion
Takahiro Kusano, Pujana Paliyawan, Tomohiro Harada, Ruck Thawonmas · 2017
This paper proposes a motion-gaming AI for health promotion that can adapt to the player's behavior change in an effective manner. Through modeling of the player's behavior and predicting of their counteraction, this AI learns how its actions can induce its opponent player to move. The proposed AI aims at suppressing health risks associated with motion gaming, by improving balancedness in use of body segments, as well as at increasing the level of calories consumption.