December 2019
Intermediate to advanced
368 pages
11h 10m
English
Content preview from Hands-On Neuroevolution with Python
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Fitness evaluation of the maze-solver agents
We estimate the fitness score of each individual in the maze-solver population as a compound consisting of two components: the novelty score and the distance to the maze exit at the end of the trajectory. The influence of each component is controlled by a coefficient pair produced by the individuals from the population of the objective function candidates.
The fitness score evaluation is divided into three functions, which we are going to discuss next.
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