University of Hertfordshire

Documents

View graph of relations
Original languageEnglish
Article number26
Number of pages25
JournalPhilosophies: Special Issue on Frontiers of Embodied Artificial Intelligence: The (r-)evolution of the embodied approach in AI
Journal publication dateJun 2019
Volume4
Issue2
Early online date23 May 2019
DOIs
Publication statusPublished - Jun 2019

Abstract

In this article, an enactive architecture is described that allows a humanoid robot to learn to compose simple actions into turn-taking behaviours while playing interaction games with a human partner. The robot’s action choices are reinforced by social feedback from the human in the form of visual attention and measures of behavioural synchronisation. We demonstrate that the system can acquire and switch between behaviours learned through interaction based on social feedback from the human partner. The role of reinforcement based on a short-term memory of the interaction was experimentally investigated. Results indicate that feedback based only on the immediate experience was insufficient to learn longer, more complex turn-taking behaviours. Therefore, some history of the interaction must be considered in the acquisition of turn-taking, which can be efficiently handled through the use of short-term memory.

ID: 17275983