Human-Robot Co-Creativity: Task Transfer on a Spectrum of Similarity

A creative robot autonomously produces a behavior that is novel for the robot or generated through a creative reasoning process. In the current state of the art in interactive robotics, while a robot may learn a task by observing a human teacher, it usually cannot later adapt what it has learned to the context of a new environment. The differences between the original, source environment and the new, target environment lie on a spectrum of similarity and have a direct impact on the difficulty of the transfer problem. We examine a subset of transfer problems in which the robot must exhibit creative behavior in order to perform in the new environment successfully. We argue that for transfer problems in which the source and target environments are sufficiently different, creativity is necessary for successful task transfer. To address such problems, we propose the use of human-robot co-creativity as a framework for collaboration between the human teacher and the robot learner in order to address task transfer.