Abstract. Dynamic Bayesian networks (DBNs) extend Bayesian networks from static domains to dynamic domains. The only known generic method for exact inference in DBNs is based on dy...
During past few years, a variety of methods have been developed for learning probabilistic networks from data, among which the heuristic single link forward or backward searches ar...
A variety of hybrid genetic algorithms has been recently proposed to address the vehicle routing problem with time windows (VRPTW), a problem known to be NP-hard. However, very few...
This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...
The evaluation of a large implemented natural language processing system involves more than its application to a common performance task. Such tasks have been used in the message u...
Noun phrases carry much of the information in a text. Systems that attempt to acquire knowledge from text must first decompose complex noun phrases to get access to that informatio...
Abstract. The general timetabling problem is an assignment of activities to xed time intervals, adhering to a prede ned set of resource availabilities. Timetabling problems are di ...
We present ELEM2, a new method for inducing classification rules from a set of examples. The method employs several new strategies in the induction and classification processes to ...