We analyzed texts from years 1800-2004 from the Philosophical Transactions of the Royal Society of London. Two-thousand-word sections from about 20 articles published at 25-year i...
Michell Bruss, Michael J. Albers, Danielle McNamer...
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
Methods for discovering causal knowledge from observational data have been a persistent topic of AI research for several decades. Essentially all of this work focuses on knowledge...
Marc Maier, Brian Taylor, Huseyin Oktay, David Jen...
We consider the frame problem, that is, char acterizing the assumption that properties tend to persist over time. We show that there are at least three distinct assumptions that...
Many applications of knowledge discovery and data mining such as rule discovery for semantic query optimization, database integration and decision support, require the knowledge t...