Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
In this paper we describe PADUA, a protocol designed to enable agents to debate an issue drawing arguments not from a knowledge base of facts, rules and priorities but directly fro...
Maya Wardeh, Trevor J. M. Bench-Capon, Frans Coene...
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
: In the context of knowledge management, we focus on the representation and the retrieval of past experiences called cases within the Case-Based Reasoning (CBR) paradigm. CBR is a...
Recent researches have demonstrated the importance of concept map and its versatile applications especially in e-Learning. For example, while designing adaptive learning materials...