A generic and extendible Multi-Agent Data Mining (MADM) framework, EMADS (the Extendible Multi-Agent Data mining System) is described. The central feature of the framework is that ...
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
Developing multi-agent simulations seems to be rather straight forward, as active entities in the original correspond to active agents in the model. Thus plausible behaviors can be...
A fundamental task in multi-agent systems is matchmaking, which is to retrieve and classify service descriptions of agents that (best) match a given service request. Several approa...
Features are essential characteristic of applications within a product line. Features organized in different kinds of diagrams containing hierarchies of feature trees are closely ...