Dear all, During the last week, I finished the implementation of gene, genome (the critical part) for CNE algorithm. Now I am going to do a PR for the two classes after making sure there is no error.
Before submitting my code to mlpack repository, I update it frequently on my local forked repository. If you are interested, you can check it at https://github.com/BangLiu/mlpack/tree/ne/src/mlpack/methods/ne This week I will focusing on come up with a good abstraction of CNE algorithm and test it with XOR test. Best, Bang 2016-05-30 17:23 GMT-06:00 bang liu <[email protected]>: > Dear all, > > I am working on the project "Neuroevolution Algorithms Implementation". > > This week, I am working on the implementation of Conventional > Neuro-evolution (CNE): weight evolution on topologically fixed neural > networks. As the first step, I am implementing classes corresponding to the > concepts in NE algorithms, including: gene, genome, population and CNE. > Currently, the implementation of gene is finished and tested, and the other > classes' implementation are in progress. > > The main reference papers for the implementation of CNE includes: > [1] "Training Feedforward Neural Networks Using Genetic Algorithms > <http://www.ijcai.org/Proceedings/89-1/Papers/122.pdf>" > [2] "Evolving Artificial Neural Networks > <http://www.cs.bham.ac.uk/~axk/evoNN.pdf>" > > I will continue implementing the CNE algorithm in this week and hopefully > submit my first PR to mlpack. After finished the implementation of a > specific algorithm, I will summarize the implementation by mlpack blog. > > Best, > Bang >
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