July 29, 2020 | 42nd Annual Meeting of the Cognitive Science Society
For all their recent successes, artificial systems do not yet perform basic commonsense reasoning at the level of even young children. By understanding the origins of common sense in humans, we hope to understand how to recapitulate it in machines. In turn, by looking at the successes and failures of machines, we can make scientific progress towards understanding the initial state and learning mechanisms of human intelligence.
This workshop serves as a forum for considering theories and approaches for understanding and building common sense, presenting experimental research that probes the foundations of common sense in people, and reporting on progress on building artificial agents with infant-like commonsense reasoning capabilities.
While the workshop is over, videos of each of the speakers are linked below in the Talks section.
|Alan Fern||A model-based reinforcement learning perspective on common sense learning|
|Stanislas Dehaene||Advances in understanding human geometrical intuition|
|Joshua Tenenbaum||Tools for reverse engineering common sense|
|Ori Ossmy||A behavioral approach to the development of common sense|
|Matthew Botvinick||Learning intuitive physics (almost) from scratch|
|Moira Dillon||Cognitive Artificial Intelligence: Building better machines… and babies!|
|Deepak Pathak||Intelligence without a brain|
|Jessica Sommerville||Developing a moral sense: probing the extents and limits of infants’ socio-moral cognition and behavior|
|Eliza Kosoy||Curiosity and exploration in children’s maze playing using DeepMind Lab|
|Tucker Hermans||Can common sense guide autonomous robot exploration?|
|Kevin Smith||Building models of infants’ physical understanding|
|Shari Liu||Origins of social intelligence in human infants|
|Allison Gopnik||Children are MESS-y: Model-building, Exploratory, Social learning systems|