By exploiting a gradual increase in complexity both internal and external, while reusing structures and information gained from previously learned behaviors, we hope to be able to learn increasingly sophisticated behaviors. We believe that these methods will allow us to construct systems which scale autonomously. Social Interaction Human infants are extremely dependent on their caregivers, relying upon them not only for basic necessities but also as a guide to their development. Building social skills into an artificial intelligence provides not only a natural means of human-machine interaction but also a mechanism for bootstrapping more complex behavior. Our research program has investigated social interaction both as a means for bootstrapping and as an instance of developmental progression.
Social interaction can be a means to facilitate learning.
New skills may be socially transferred from caregiver to infant through mimicry or imitation, through direct tutelage, or by means of scaffolding, in which a more able adult manipulates the infant's interactions with the environment to foster novel abilities. Commonly scaffolding involves reducing distractions, marking the task's critical attributes, reducing the number of degrees of freedom in the target task, and enabling the infant to experience the end or outcome before she is cognitively or physically able of seeking and attaining it for herself. We are currently engaged in work studying bootstrapping new behaviors from social interactions . The social skills required to make use of scaffolding are complex. Infants acquire these social skills through a developmental progression.