Art-Based Autonomous Learning Systems: Part I — Architectures and Algorithms
Chee Peng Lim, Robert F. Harrison · Studies in fuzziness and soft computing · 2000
This chapter describes the design of novel ART-based intelligent systems that are able to learn and, at the same time, to refine their knowledge in perpetuity. Fuzzy ARTMAP and the Probabilistic Neural Network are integrated to form a hybrid system that possesses the desirable properties for incremental, causal learning as well as for Bayesian probability estimation. Subsequently, a multiple neural network architecture is devised to aggregate outputs from several individual networks into a unified decision. A number of algorithms is proposed to increase the generalization and adaptability of the resulting systems. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.