Learning and using relational theories

Much of human knowledge is organized into sophisticated systems that are often called intuitive theories. We propose that intuitive theories are mentally represented in a logical language, and that the subjective complexity of a theory is determined by the length of its representation in this language. This complexity measure helps to explain how theories are learned from relational data, and how they support inductive inferences about unobserved relations. We describe two experiments that test our approach, and show that it provides a better account of human learning and reasoning than an approach developed by Goodman [1]. What is a theory, and what makes one theory better than another? Questions like these are of obvious interest to philosophers of science but are also discussed by psychologists, who have argued that everyday knowledge is organized into rich and complex systems that are similar in many respects to scientific theories. Even young children, for instance, have systema...

• Type: Conference
• Year: 2007
• Where: NIPS
• Authors: Charles Kemp, Noah Goodman, Joshua B. Tenenbaum
• Keywords: Information Technology, Intuitive Theories, NIPS 2007, Scientific Theories, Subjective Complexity