Logistic classifier

The logistic classifier will be applied to lv (the six location values) to find the best location for the AGV. It is based on the output of the six neurons (input x weight + bias).

What are logistic functions? The goal of a logistic classifier is to produce a probability distribution from 0 to 1 for each value of the output vector. As you have seen so far, AI applications use applied mathematics with probable values, not raw outputs. In the warehouse model, the AGV needs to choose the best, most probable location, l_i. Even in a well-organized corporate warehouse, many uncertainties (late arrivals, product defects, or a number of unplanned problems) reduce the probability of a choice. A probability represents a value between 0 (low probability) and 1 (high probability). Logistic functions provide the tools to convert all numbers into probabilities between 0 and 1 to normalize data.