Title :
Learning polite behavior with situation models
Author :
Barraquand, R?©mi ; Crowley, James L.
Author_Institution :
INRIA Grenoble Res. Center, INP Grenoble, St. Ismier, France
Abstract :
In this paper, we describe experiments with methods for learning the appropriateness of behaviors based on a model of the current social situation. We first review different approaches for social robotics, and present a new approach based on situation modeling. We then review algorithms for social learning and propose three modifications to the classical Q-Learning algorithm. We describe five experiments with progressively complex algorithms for learning the appropriateness of behaviors. The first three experiments illustrate how social factors can be used to improve learning by controlling learning rate. In the fourth experiment we demonstrate that proper credit assignment improves the effectiveness of reinforcement learning for social interaction. In our fifth experiment we show that analogy can be used to accelerate learning rates in contexts composed of many situations.
Keywords :
learning (artificial intelligence); robots; social aspects of automation; Q-learning algorithm; credit assignment; polite behavior; reinforcement learning; situation modeling; social factors; social learning; social robotics; social situation; Convergence; Humans; Learning; Machine learning; Robot sensing systems; Standards; Credit assignment; Learning by Analogy; Q-Learning; Social Interaction; Social Learning; Social Robotics;
Conference_Titel :
Human-Robot Interaction (HRI), 2008 3rd ACM/IEEE International Conference on
Print_ISBN :
978-1-60558-017-3