Alison Gopnik - Casual Learning in Children and Computational Models

Very young children routinely solve causal problems that are still very challenging for machine learning systems. I will outline several exciting recent lines of work looking at young children’s causal reasoning and learning and comparing it to learning in various computational models. This includes work on the selection of relevant test variables, learning abstract and analogical relationships, and, most importantly, techniques for active learning and causal exploration.