The maze navigation is a classic computer science problem related to the autonomous navigation domain. In this chapter, you will learn how neuroevolution-based methods can be used to solve the challenge of maze navigation. Also, we will explain how to define a goal-oriented fitness function using the fitness scores of the navigator agent calculated as a derivative of the agent's distance from the final goal. By the end of this chapter, you will understand the basics of training an autonomous navigation agent using neuroevolution methods and will be able to create the more advanced maze solver that will be introduced in the next chapter. You will become familiar with advanced visualization techniques that will make it easier to understand the results of algorithm execution. Also, you will obtain hands-on experience of writing simulators of maze-navigating...
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