This paper presents an innovative multiagent system to support cooperative learning among students both in the real classrooms and in distance education. The system, called I-MIND...
Modeling learning agents in the context of Multi-agent Systems requires an adequate understanding of their dynamic behaviour. Usually, these agents are modeled similar to the di...
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
In this paper we demonstrate how weighted majority voting with multiplicative weight updating can be applied to obtain robust algorithms for learning binary relations. We first pre...
In this paper, we look at a supply chain of commodity goods where customer demand is uncertain and partly based on reputation, and where raw material replenishment is uncertain in...