Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agent’s Location Using Hidden Markov Models

Abstract EN

We propose to use a supervised machine learning technique to track the location of a mobile agent in real time.

Hidden Markov Models are used to build artificial intelligence that estimates the unknown position of a mobile target moving in a defined environment.

This narrow artificial intelligence performs two distinct tasks.

First, it provides real-time estimation of the mobile agent’s position using the forward algorithm.

Second, it uses the Baum–Welch algorithm as a statistical learning tool to gain knowledge of the mobile target.

Finally, an experimental environment is proposed, namely, a video game that we use to test our artificial intelligence.

We present statistical and graphical results to illustrate the efficiency of our method.