The softmax function appears in many artificial intelligence models to normalize data. This is a fundamental function to understand and master. In the case of the warehouse model, an AGV needs to make a probable choice between six locations in the lv vector. However, the total of the lv values exceeds 1. lv requires normalization of the softmax function S. In this sense, the softmax function can be considered as a generalization of the logistic sigmoid function. In the code, lv vector will be named y.
The following code used is SOFTMAX.py; y represents the lv vector in the following source code.
# y is the vector of the scores of ...
