Neural Networks: Single-Layer Control

This lecture covers the implementation of a single-layer neural network controller using Webots simulation software. It explains the differences between artificial neurons, perceptrons, and single-layer neural networks. The lecture also discusses transfer functions, the addition of a third sensor, and the impact of sensor numbers on behavior complexity. Furthermore, it explores the efficiency of neuron usage, dataset generation, and varying network architectures in solving tasks. The session concludes with an overview of Boids rules for collective behavior.