Computational Sensorimotor Learning

Colloquium | May 4 | 12:30-1:30 p.m. | 250 Sutardja Dai Hall

 Pulkit Agrawal, UC Berkeley

 Electrical Engineering and Computer Sciences (EECS)

An open question in artificial intelligence is how to endow agents with common sense knowledge that humans naturally seem to possess. A prominent theory in child development posits that human infants gradually acquire such knowledge by the process of experimentation. According to this theory, even the seemingly frivolous play of infants is a manifestation of experiments conducted by them to learn about their environment. Inspired by this view of biological sensorimotor learning, I will present my work on building artificial agents that use the paradigm of experimentation to explore and condense their experience into models that enable them to solve new problems. I will discuss the effectiveness of my approach and open issues using case studies of a robot learning to push objects, manipulate ropes, finding its way in office environments and an agent learning to play video games merely based on the incentive of conducting experiments.