  In this article, an enactive architecture is described that allows a humanoid
robot to learn to compose simple actions into turn-taking behaviors 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 behavioral synchronization. We demonstrate that the system can
acquire and switch between behaviors learned through interaction based on
social feedback from the human partner. The role of reinforcement based on a
short term memory of the interaction is experimentally investigated. Results
indicate that feedback based only on the immediate state is insufficient to
learn certain turn-taking behaviors. 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.
