Computational Sensorimotor Learning
Colloquium: EE: CS | May 4 | 12:30-1:30 p.m. | 250 Sutardja Dai Hall
Pulkit Agrawal, UC Berkeley
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.