I am interested in how humans develop category knowledge. How do people encode and organize information in memory, and how do they retrieve information to make intelligent decisions? I study these questions by conducting experiments that examine how humans learn from examples and fitting computational models to the observed data.

A series of experiments showed that people better remember objects that violate a regularity (e.g., bats) than objects that follow the regularity (e.g., robins). The simulation results of various types of computational models of category learning suggest that models need a clustering mechanism to account for the observed enhanced oddball memory.

Sakamoto, Y., & Love, B. C. (2006). Vancouver, Toronto, Montreal, Austin: Enhanced oddball memory through differentiation, not isolation. Psychonomic Bulletin & Review, 13, 474-479.

Sakamoto, Y., & Love, B. C. (2004). Schematic influences on category learning and recognition memory. Journal of Experimental Psychology: General, 133, 534-553.

[ Context model ] [ RULEX ] [ SUSTAIN ] - Python code

How do people cluster objects and events? They group similar things together. Whether two things are similar to each other depends on situations. For example, People's knowledge of the same category can be organized differently when they engage in different tasks and have different goals. People shift attention to information that is critical for a given task, which influences their perception of the world.

Sakamoto, Y., & Love, B. C. (2006). Sizable sharks swim swiftly: Learning correlations through inference in a classroom setting. In R. Sun and N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society. Vancouver, Canada: Cognitive Science Society.

Sakamoto, Y., Matsuka, T., & Love, B. C. (2004). Dimension-wide vs. exemplar-specific attention in category learning and recognition. In M. Lovett, C. Schunn, C. Lebiere, and P. Munro (Eds.), Proceedings of the 6th International Conference on Cognitive Modeling (pp. 261-266). Mahwah, NJ: Lawrence Erlbaum.

People's perception of category variability is influenced by the sequence of encountering category members. Thus, people are updating their memory representations in a local trial-by-trial fashion.

Sakamoto, Y., Love, B. C., & Jones, M. (2006). Tracking Variability in Learning: Contrasting Statistical and Similarity-Based Accounts. In R. Sun and N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society. Vancouver, Canada: Cognitive Science Society.

[ Context model ] - Python code