Three-Subagent Adapting Architecture for Fighting Videogames

In standard fighting videogames, since opponents controlled by computers are in a rut, the user has learned their behaviors after long play and gets bored. Thus we propose an adapting opponent with three subagent architecture that adapts to the level of the user by reinforcement learning. The opponent was evaluated by human users by comparing it against static opponents.