Causal Learning: Psychology, Philosophy, and Computation

Understanding causal structure is a central task of human cognition. Causal learning underpins the development of our concepts and categories, our intuitive theories, and our capacities for planning, imagination and inference. During the last few years, there has been an interdisciplinary revolution in our understanding of learning and reasoning: Researchers in philosophy, psychology, and computation have discovered new mechanisms for learning the causal structure of the world. This new work provides a rigorous, formal basis for theory theories of concepts and cognitive development, and moreover, the causal learning mechanisms it has uncovered go dramatically beyond the traditional mechanisms of both nativist theories, such as modularity theories, and empiricist ones, such as association or connectionism.

Alison Gopnik is Professor of Psychology at the University of California at Berkeley. She is the coauthor of Words, Thoughts and Theories (1997), and The Scientist mn the Crib (1999). She has written over a hundred scientific articles as well as articles for The New York Times, The New York Review of Books and Slate.com.

Laura Schulz is Assistant Professor of Brain and Cognitive Sciences at the Massachussets Institute of Technology. She has been the recipient of National Science Foundation and American Association of University Women fellowships. She has published in Developmental Psychology, Child Development, Psychological Review and Trends in Cognitive Sciences.