RAM based methods

This section introduces the reader to some of the major RAM based methods. The first paper presents an overview of the RAM based methods up to 1994. It covers the most well known methods in RAM based networks. This paper is followed by an overview of the MAGNUS system, introduced by Igor Aleksander who has been one of the major influences in the development of RAM based systems throughout the last 30 years. The paper shows how RAM based systems in the form of WISARD is related to MAGNUS, a system designed to explore possibility of systems that react in an intelligent way to sensory data. The paper by DeCarvaho, Fairhirst and Bisset describes a form of RAM learning called GSN^f which allows training of multi-layered RAM based systems, and aims to compare the various forms of the GSN methods. The final paper generally introduces the AURA RAM based network, which extends the RAM based method for use in rule based systems, which is an unusual application for neural networks but exploits the speed and flexibility of the RAM based method for this task.