In case-based reasoning (CBR) a problem is solved by matching the problem description to a previously solved case, using the past solution in solving the new problem. A case-based...
In this paper we present an approach for reducing the memory footprint requirement of temporal difference methods in which the set of states is finite. We use case-based generaliza...
This paper introduces a hierarchical Markov model that can learn and infer a user's daily movements through the commue model uses multiple levels of abstraction in order to b...
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
Abstract. The high level of abstraction necessary to teach data structures and algorithmic schemes has been more than a hindrance to students. In order to make a proper approach to...