Applying Multiple Classifier Systems to SoftMan's Perception System

Abstract

SoftMan, the virtual robot in network environment, is a kind of software Artificial Life living in computer networks. It has a humanoid structure, and simulating human, its perception system should be able to recognize perceptive objects. Enlightened by human's perception system and the "disassemble-integration" method in analyzing large systems, a cooperative classification model in SoftMan's perception system is proposed. In the model, different humanoid senses are simulated by multiple classifier systems (MCS). Consequently, SoftMan can perform multi-sense cooperative classification on its perceptive objects. A simulated experiment validates the basic feasibility of the model.