Uniting "a priori" and "a posteriori" knowledge: A research framework
published: Aug. 3, 2009, recorded: July 2009, views: 3972
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
The ability to perform machine classification is a critical component of an intelligent system. We propose to unite the logical, a priori approach to this problem with the empirical, a posteriori approach. We describe in particular how the a priori knowledge encoded in Cyc can be merged with technology for probabilistic inference using Markov logic networks. We describe two problem domains – the Whodunit Problem and noun phrase understanding – and show that Cyc’s commonsense knowledge can be fruitfully combined with probabilistic reasoning.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !