Computational philosophy of science
Computational philosophy of science
Search: A survey of recent results
Exploring artificial intelligence
Machine discovery in chemistry: new results
Artificial Intelligence
From contingency tables to various forms of knowledge in databases
Advances in knowledge discovery and data mining
How to solve it: modern heuristics
How to solve it: modern heuristics
Representation reducing heuristics for semi-automated scientific discovery
Representation reducing heuristics for semi-automated scientific discovery
Towards an integrated discovery system
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
Checking scientific assumptions by modeling
DS'06 Proceedings of the 9th international conference on Discovery Science
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Scientists need customizable tools to help them with discovery. We present an adjustable heuristic function for scientific discovery. This function may be considered in either a Minimum Message Length (MML) or a Bayesian Net manner. The function is approximate because the default method of specifying theory prior probabilities is a gross estimate and because there is more to theory choice than maximizing probability. We do, however, effectively capture some user preferences with our technique. We show this for the qualitatively different domains of geophysics and sociology.