This paper explores the application of the Minimum Description Length principle for pruning decision trees. We present a new algorithm that intuitively captures the primary goal o...
The Prism family of algorithms induces modular classification rules which, in contrast to decision tree induction algorithms, do not necessarily fit together into a decision tree s...
We show how the understandability and speed of genetic programming classification algorithms can be improved, without affecting the classification accuracy. By analyzing the dec...
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
The belief decision tree (BDT) approach is a decision tree in an uncertain environment where the uncertainty is represented through the Transferable Belief Model (TBM), one interp...