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Telecommunications systems and Neural Network (NN) systems have a lot in common, and any programming language that was created for one, by extension is applicable to the other. This presentation covers how Erlang's various features make it a powerful NN programming language which gives us an ability to develop highly scalable, and fully distributed Neural Network and parallel genetic algorithm systems. An exploration of the new functionality that Erlang can add to Computational Intelligence systems will be discussed. Finally, a case study of DXNN, the first and highly efficient Topology and Weight Evolving Artificial Neural Network developed purely in Erlang, will be presented and analysed.

Target audience: Computational Intelligence researchers, Erlang programmers, and anyone that is generally interested in developing soft computing systems.

Talk objective: To elucidate and discuss Erlang's applicability to the development of scalable computational intelligence systems.