Adaptive Motion Gaming AI for Health Promotion
April 04, 2017 Β· Declared Dead Β· π AAAI Spring Symposia
"No code URL or promise found in abstract"
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Authors
Pujana Paliyawan, Takahiro Kusano, Yuto Nakagawa, Tomohiro Harada, Ruck Thawonmas
arXiv ID
1704.00961
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CY,
cs.HC
Citations
7
Venue
AAAI Spring Symposia
Last Checked
4 months ago
Abstract
This paper presents a design of a non-player character (AI) for promoting balancedness in use of body segments when engaging in full-body motion gaming. In our experiment, we settle a battle between the proposed AI and a player by using FightingICE, a fighting game platform for AI development. A middleware called UKI is used to allow the player to control the game by using body motion instead of the keyboard and mouse. During gameplay, the proposed AI analyze health states of the player; it determines its next action by predicting how each candidate action, recommended by a Monte-Carlo tree search algorithm, will induce the player to move, and how the player's health tends to be affected. Our result demonstrates successful improvement in balancedness in use of body segments on 4 out of 5 subjects.
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