December 2019
Intermediate to advanced
368 pages
11h 10m
English
Content preview from Hands-On Neuroevolution with Python
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Exercise 1
- Set the population size (pop_size) parameter in the maze_config.ini file to 250. See if the maze solver can be found in this case.
- Change the value of the parameter specifying the probability of adding a new node (node_add_prob). Was the neuroevolution process able to find a solution, and is it optimal from a topological point of view?
- Change the initial genome configuration to have zero hidden nodes at the beginning (num_hidden). How does this affect the algorithm's performance?
- Try to use another novelty metric that is provided with the source code (maze.maze_novelty_metric_euclidean) and see what happens.
- Change the location_sample_rate command-line parameter from its default value (4000), which allows you to include only ...
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