December 2019
Intermediate to advanced
368 pages
11h 10m
English
Content preview from Hands-On Neuroevolution with Python
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The trials cycle
In this chapter, we introduce an upgrade to the experiment runner implementation. We implement support to run multiple trials sequentially until the solution is found. Such an upgrade dramatically simplifies working with the multiple experiment trials sequentially, especially taking into account that each trial can take a long time to execute.
The main cycle of the experiment runner now looks like this (see __main__ in the maze_experiment.py script):
print("Starting the %s maze experiment (Novelty Search), for %d trials" % (args.maze, args.trials)) for t in range(args.trials): print("\n\n----- Starting Trial: %d ------" % (t)) # Create novelty archive novelty_archive = archive.NoveltyArchive( threshold=args.ns_threshold, ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.