Recurrent neural network are a promising neural network layout which provides a better performance than a normal topology, which is a three layer forward network. The main problem with recurrent neural network is to adjust the weights. Instead of testing out random weights with a brute force algorithm, the slightly faster idea is to use genetic algorithms for identifying the parameters more efficient.
A practical example which includes the pendulum problem was realized in the Java programming language. The problem with genetic algorithms is, that they can only solve simple problem, but are not useful for tackling complex problems like realtime-strategy games or robotics control application. This is the reason, why in most papers only toy problems like the inverted pendulum problem or the mountain cart are provided.
- Jonathan A. Michaels: geneticRNN: A simple genetic training algorithm for recurrent neural networks, 2018, https://github.com/JonathanAMichaels/geneticRNN
- rootmolloch: Recurrent Neural Network with genetic backtracking, https://github.com/rootmolloch/SparseLocalBacktrackingSelfGenetics