A walkthrough of building a neural network agent that plays Snake, covering state representation with 30 inputs (ray-cast obstacle detection, direction flags, food offset), a small [30,20,20,4] feedforward network with ReLU activations, and neuroevolution training using a genetic algorithm fitness function. The post traces the
Table of contents
Why Snake Is a Good Learning ProjectThe Shape of the AppStep 1: Understand What the Network SeesStep 2: Understand the Network StructureStep 3: Understand How Training Is ScoredStep 4: Trace One Decision End to EndWhat This Teaches Beyond SnakeSort: