Maintaining Awareness of the Focus of Attention of a Conversation: A Robot-Centric Reinforcement Learning Approach

Authors

Marynel Vázquez (Disney Research Pittsburgh)
Aaron Steinfeld (Carnegie Mellon University
Scott E. Hudson (Carnegie Mellon University, Disney Research Pittsburgh)

International Symposium on Robot and Human Interactive Communication (RO-MAN) 2016

August 26, 2016

sim

We explore online reinforcement learning techniques to find good policies to control the orientation of a mobile robot during social group conversations. In this scenario, we assume that the correct behavior for the robot should convey attentiveness to the focus of attention of the conversation. Thus, the robot should turn towards the speaker. Our results from tests in a simulated environment show that a new state representation that we designed for this problem can be used to find good policies for the robot. These policies can generalize across interactions with different numbers of people and can handle various levels of sensing noise.

Download File "Maintaining Awareness of the Focus of Attention of a Conversation- A Robot-Centric Reinforcement Learning Approach-Paper"
[pdf, 1.82 MB]

Copyright Notice

The documents contained in these directories are included by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.