Models of Human Scientific Discovery
- Robert Goldstone, Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, United States
- Alison Gopnik, Department of Psychology, University of California at Berkeley, Berkeley, California, United States
- Paul Thagard, Department of Philosophy, University of Waterloo, Waterloo, Ontario, Canada
- Tomer D. Ullman, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
AbstractThe scientific understanding of scientific understanding has been a long-standing goal of cognitive science. A satisfying formal model of human scientific discovery would be a major intellectual achievement, requiring solutions to core problems in cognitive science: the creation and use of apt mental models, the prediction of the behavior of complex systems involving interactions between multiple classes of elements, high-level perception of noisy and multiply interpretable environments, and the active interrogation of a system through strategic interventions on it – namely, via experiments. Over the past decades there have been numerous attempts to build formal models that capture what Perkins (1981) calls some of the “mind’s best work” – scientific explanations for how the natural world works by systematic observation, prediction, and testing. The purpose of this symposium is to present some promising recent examples of models of scientific discovery, and describe their applications to advancing both scientific understanding and our understanding of science.
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