Evolving Universal Learning Networks Through Erlang

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This talk will cover the use of Erlang in the development of Neural
Networks, and other types of evolving learning graphs (Universal
Learning Networks). The talk will elaborate on why Erlang is a perfect
fit for the development of distributed learning networks, the importance
of Erlang’s features to the field of Computational Intelligence, and
provide a case study of its use in the construction of distributed
topology and parameter evolving universal learning network called DXNN.

Talk objectives: To discuss the utility, applicability, and effectiveness of Erlang within the field of Computational Intelligence development, and to provide a case study of using Erlang to develop a scalable universal learning network.
Target audience: Computational Intelligence researchers and enthusiasts, Erlang programmers and anyone that is generally interested in developing soft computing systems.


  • Gene Sher

    Neuroevolution Through Erlang

    Gene is a computational intelligence researcher and the inventor of DXNN, a highly efficient Topology and Weight Evolving Artificial Neural Network.

    Gene Sher
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Posted on March 26, 2012