Proceedings of the Annual Meeting of the Cognitive Science Society

Models of concept learning and theory acquisition often in-voke a stochastic search process, in which learners generatehypotheses through some structured random process and thenevaluate them on some data measuring their quality or value.To be successful within a reasonable time-frame, these mod-els need ways of generating good candidate hypotheses evenbefore the data are considered. Schulz (2012a) has proposedthat studying the origins of new ideas in more everyday con-texts, such as how we think up new names for things, can pro-vide insight into the cognitive processes that generate good hy-potheses for learning. We propose a simple generative modelfor how people might draw on their experience to proposenew names in everyday domains such as pub names or actionmovies, and show that it captures surprisingly well the namesthat people actually imagine. We discuss the role for an anal-ogous hypothesis-generation mechanism in enabling and con-straining causal theory learning.