December 2019
Intermediate to advanced
368 pages
11h 10m
English
Content preview from Hands-On Neuroevolution with Python
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The simulation cycle
Now we have fully implemented the equations of motion and the numerical approximation of the state variables for one step of the cart-pole apparatus simulation. With this, we are ready to start the implementation of a full simulation cycle, which uses the ANN of the controller to evaluate the current system state and to select the appropriate action (the force to be applied) for the next step. The ANN mentioned previously is created for each genome of the population for a particular generation of evolution, allowing us to evaluate the performance of all genomes.
Refer to the run_cart_pole_simulation(net, max_bal_steps, random_start=True) function implementation for complete implementation details.
We can refer to the ...
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