A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...
Background: More and more disordered regions have been discovered in protein sequences, and many of them are found to be functionally significant. Previous studies reveal that dis...
A decision process in which rewards depend on history rather than merely on the current state is called a decision process with non-Markovian rewards (NMRDP). In decisiontheoretic...
Incremental pattern discovery targets streaming applications where the data continuously arrive incrementally. The questions are how to find patterns (main trends) incrementally; ...