The Impact of Humanoid Affect Expression on Human Behavior in a Game-Theoretic Setting
This addresses human-robot interaction challenges by exploring mood influence in strategic games, but it is a pilot study with incremental contributions.
The study tackled how a humanoid robot's mood expression affects human decision-making in a game-theoretic setting, finding that the robot's generated affective sentences influenced the human's behavioral model, though specific numerical results were not provided.
With the rapid development of robot and other intelligent and autonomous agents, how a human could be influenced by a robot's expressed mood when making decisions becomes a crucial question in human-robot interaction. In this pilot study, we investigate (1) in what way a robot can express a certain mood to influence a human's decision making behavioral model; (2) how and to what extent the human will be influenced in a game theoretic setting. More specifically, we create an NLP model to generate sentences that adhere to a specific affective expression profile. We use these sentences for a humanoid robot as it plays a Stackelberg security game against a human. We investigate the behavioral model of the human player.