Combining causal and similarity-based reasoning

Part of Advances in Neural Information Processing Systems 19 (NIPS 2006)

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Charles Kemp, Patrick Shafto, Allison Berke, Joshua Tenenbaum


Everyday inductive reasoning draws on many kinds of knowledge, including knowledge about relationships between properties and knowledge about relationships between objects. Previous accounts of inductive reasoning generally focus on just one kind of knowledge: models of causal reasoning often focus on relationships between properties, and models of similarity-based reasoning often focus on similarity relationships between objects. We present a Bayesian model of inductive reasoning that incorporates both kinds of knowledge, and show that it accounts well for human inferences about the properties of biological species.