Much of human knowledge is organized into sophisticated systems that are often called intuitive theories. We propose that intuitive theories are mentally represented in a logical ...
We describe an application of AI search and information visualization techniques to the problem of school redistricting, in which students are assigned to home schools within a co...
Marie desJardins, Blazej Bulka, Ryan Carr, Andrew ...
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
We present a general Multi-Agent System framework for distributed data mining based on a Peer-toPeer model. The framework adopts message-based asynchronous communication and a dyn...
Program transformation through the repeated application of simple rewrite rules is conducive to formal verification. In practice, program transformation oftentimes requires data t...