Population of Linear Experts: Knowledge Partitioning and Function Learning

Michael L. Kalish, Stephan Lewandowsky, John K. Kruschke
2004 Psychological review  
Knowledge partitioning is a theoretical construct holding that knowledge is not always integrated and homogeneous but may be separated into independent parcels containing mutually contradictory information. Knowledge partitioning has been observed in research on expertise, categorization, and function learning. This article presents a theory of function learning (the population of linear experts model-POLE) that assumes people partition their knowledge whenever they are presented with a complex
more » ... task. The authors show that POLE is a general model of function learning that accommodates both benchmark results and recent data on knowledge partitioning. POLE also makes the counterintuitive prediction that a person's distribution of responses to repeated test stimuli should be multimodal. The authors report 3 experiments that support this prediction.
doi:10.1037/0033-295x.111.4.1072 pmid:15482074 fatcat:tehdeyasgfeblazcpmjo66h344