MULTIPLE-AGENT ARCHITECTURES FOR THE CLASSIFICATION OF HANDWRITTEN TEXT

Novel pattern recognition techniques using multiple agents for the recognition of handwritten text are proposed in this paper. The concept of intelligent agents and innovative multi-agent architectures for pattern recognition tasks is introduced for combining and elaborating the classification hypotheses of several classifiers. The architecture of a distributed digit-recognition system dispatching recognition tasks to a set of recognizers and combining their results is presented. This concept is being developed in the MAPR project, where intelligent agent architectures are built for pattern recognition tasks.