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Last Updated: July 2012

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George Kachergis
Graduate Student

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Bio Sketch

I am generally interested in uncovering fundamental mechanisms of learning, memory, and categorization, and in how they interact. In the MAPLAB, I have carried out a number of cross-situational statistical learning experiments, in which participants attempt to learn word-object mappings over a series of individually ambiguous trials. That is, each trial displays several objects, and several words are played in a random order, so the correct mappings may only be guessed. Thus, the correct pairs may only be disambiguated by accumulating word-object co-occurrence information over the entire trial sequence (across situations). In this paradigm, proposed by Chen Yu and Linda Smith, I have designed and conducted experiments on implicit learning, categorization, contextual diversity, frequency, eye-tracking, and much more. My focus has shifted to modeling this data.

Representative Publications
Kachergis, G., Yu, C., & Shiffrin, R. M. (2012). An Associative Model of Adaptive Inference for Learning Word-Referent Mappings. Psychonomic Bulletin & Review, 19(2), 317-324. [web] [pdf]
Kachergis, G. (2012). Learning Nouns with Domain-General Associative Learning Mechanisms. Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. xxx). Austin, TX: Cognitive Science Society. [pdf]
Kachergis, G., Yu, C., & Shiffrin, R. M. (2009) Frequency and Contextual Diversity Effects in Cross-Situational Word Learning. In N. Taatgen, H. van Rijn, J. Nerbonne, & L. Schomaker (Eds.) Proceedings of the 31st Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. [pdf]