Learning and Representation in Cognition
Lab Director:
Research Areas: cognitive science; computational cognition; concepts and categories; similarity and analogy; neural network models of cognition; machine learning; transfer; science of learning.
A key purpose of the cognitive activity in the human mind is making sense of the world around us. To scientifically account for this process of ordering our experience, we must address:
how is knowledge used as a basis for comprehension and reasoning?
how is such knowledge acquired and organized?
Much of the work in our laboratory focuses on two cognitive mechanisms that serve as a bridge between perpetual experience and stored knowledge: categorization is the process of interpreting an example as a member of a known class or concept; and comparison is the process of interpreting an example with respect to (or in light of) another. Categorization of comparison processes not only serve to guide interpretation in terms of prior knowledge, but they can also guide learning or conceptual change by updating the knowledge itself. Our work in the lab consists of behavioral studies of the nature and roles of categorization and comparison along with: 1) the development of neural network models to instantiate theoretical claims and simulate human learning and cognitive performance; and 2) work under a computational cognition framework to advance the study of learning and reasoning in minds and machines.