行为科学高端论坛（四）【12月6日周二，15:00-16:30，南楼5层会议室】：行为科学高端论坛（四）【12月6日周二，15:00-16:30，南楼5层会议室】：Chance and Time
报告主题：Chance and Time
The brain’s ability to perceive patterns out of randomness is an essential aspect of human intelligence, as well as an active research topic in Artificial Intelligence and Machine Learning. Ironically, the ability is also often blamed for underlying many of the so-called cognitive "biases", including the hot-hand belief and gambler’s fallacy. In this talk, I will address the issue by demonstrating the limitations of conventional mathematical frameworks such as probability theory for modeling human cognition. I will show how a biologically motivated neural network can learn not only how likely a pattern occurs (chance) but also how soon a pattern is to occur (time), and therefore is capable of capturing much richer statistical structures that are important for survival. I will advocate the need for a new mathematics for modeling the brain and the mind that is simultaneously descriptive, normative, and biologically realistic. Quantum approach to cognition will be discussed.
Hongbin Wang, Ph.D., professor and co-director, Center for Biomedical Informatics, Texas A&M University College of Medicine. He graduated with a BS in psychology from Peking University, and received a MS in computer science and a PhD in psychology, both from the Ohio State University. His research is in the area of cognitive science and cognitive computing. His recent research interests include the neuro-computational foundation of human decision making and machine intelligence.