TY - JOUR
T1 - An intelligent fighting videogame opponent adapting to behavior patterns of the user
AU - Moriyama, Koichi
AU - Ortiz Branco, Simón Enrique
AU - Matsumoto, Mitsuhiro
AU - Fukui, Ken Ichi
AU - Kurihara, Satoshi
AU - Numao, Masayuki
PY - 2014
Y1 - 2014
N2 - In standard fighting videogames, users usually prefer playing against other users rather than against machines because opponents controlled by machines are in a rut and users can memorize their behaviors after repetitive plays. On the other hand, human players adapt to each other's behaviors, which makes fighting videogames interesting. Thus, in this paper, we propose an artificial agent for a fighting videogame that can adapt to its users, allowing users to enjoy the game even when playing alone. In particular, this work focuses on combination attacks, or combos, that give great damage to the opponent. The agent treats combos independently, i.e., it is composed of a subagent for predicting combos the user executes, that for choosing combos the agent executes, and that for controlling the whole agent. Human users evaluated the agent compared to static opponents, and the agent received minimal negative ratings.
AB - In standard fighting videogames, users usually prefer playing against other users rather than against machines because opponents controlled by machines are in a rut and users can memorize their behaviors after repetitive plays. On the other hand, human players adapt to each other's behaviors, which makes fighting videogames interesting. Thus, in this paper, we propose an artificial agent for a fighting videogame that can adapt to its users, allowing users to enjoy the game even when playing alone. In particular, this work focuses on combination attacks, or combos, that give great damage to the opponent. The agent treats combos independently, i.e., it is composed of a subagent for predicting combos the user executes, that for choosing combos the agent executes, and that for controlling the whole agent. Human users evaluated the agent compared to static opponents, and the agent received minimal negative ratings.
KW - Adapting agent
KW - Entertainment computing
KW - Pattern matching
KW - Reinforcement learning
UR - http://www.scopus.com/inward/record.url?scp=84897436980&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84897436980&partnerID=8YFLogxK
U2 - 10.1587/transinf.E97.D.842
DO - 10.1587/transinf.E97.D.842
M3 - Article
AN - SCOPUS:84897436980
VL - E97-D
SP - 842
EP - 851
JO - IEICE Transactions on Information and Systems
JF - IEICE Transactions on Information and Systems
SN - 0916-8532
IS - 4
ER -