Analyzing the Performance of an Agent-based Neural System for Classification Tasks Using Data Distribution among the Agents

The use of intelligent agents in the structure of multi-classifier systems has been investigated in order to overcome some drawbacks of these systems and, as a consequence, to improve the performance of such systems. As a result of this, the NeurAge system was proposed. This system has presented good results in some conventional (centralized) classification tasks. Nevertheless, in some classification tasks, relevant features can be distributed over a set of agent. These applications can be classified as distributed classification tasks. In this paper, an investigation of the performance of the NeurAge system in distributed classification tasks will be performed. In other words, it will be investigated the performance of NeurAge when the data are distributed over its agents.