The Impact of the Collective Members’ Independence on the Prediction Accuracy

Abstract

Decision making is one of the most frequently performed processes nowadays. Our future or other people’s future may depend on the decision we make, therefore we try to take it as good as possible. The rapid development of technology facilitates it for us, as we are able to store, process and analyse more and more data. However, the power of human knowledge extended by experience and intuition still overperforms computer systems in solving such problems. The power of the combined knowledge of a group of people is known as a collective intelligence. In this paper, an analysis of one of the properties describing the consensus is presented, id est the influence between its members. The work is based on graph theory and a multi-agent system approach to formalise the problem. The new measures describing the collective and the accuracy of the final prediction were proposed. Experimental evaluations, based on the developed environment, followed by the statistical analysis of the obtained results allowed to observed four relationships between the considered measures describing the collective and the accuracy of collective prediction. The independence of the collective members plays a crucial role in the decision-making, therefore it should be carefully considered when selecting people for the collective, especially the large ones.

Keywords

• Collective intelligence
• independence
• knowledge management
• multi-agent system
• prediction