In recent years, games like Chess, Go, DOOM, and Rubik’s Cube have provided scientists platforms for studying human learning, cognition, and decision-making. Computational models from these studies illustrate how people move through, and interact with, the games. Incoming postdoctoral fellow Maell Cullen has used such experiments to model how learning and cognition vary between older and younger brains.
“Now you can simulate unwieldy models with more and more complexity,” says Cullen. “But if, midway through, you stop and ask that model “why did you make that decision,” you can’t. They’re black boxes.”
Cullen, whose research interests include theoretical neuroscience and machine learning, wants to develop better computational models that provide insight into what happens between perception and action — to see the “why” inside that black box.
During his fellowship at SFI, Cullen will be part of SFI’s Complex Time — Adaptation, Aging, and the Arrow of Time research theme, working with President David Krakauer, External Professor John Krakauer (Johns Hopkins), and Adrian Haith (Johns Hopkins) to explore the acquisition and loss of skills and cognitive ability, and what characteristics underlie expert-level game performance.
Cullen holds a Ph.D. in engineering mathematics from the University of Bristol, an M.Sc. in computational intelligence from Ulster University, and a B.Sc. in neuroscience and smart systems from Keele University.