We propose to use a supervised machine learning technique to track the location of a mobile agent in real time. Hidden Markov\nModels are used to build artificial intelligence that estimates the unknown position of a mobile target moving in a defined\nenvironment. This narrow artificial intelligence performs two distinct tasks. First, it provides real-time estimation of the mobile\nagentââ?¬â?¢s position using the forward algorithm. Second, it uses the Baumââ?¬â??Welch algorithm as a statistical learning tool to gain\nknowledge of the mobile target. Finally, an experimental environment is proposed, namely, a video game that we use to test our\nartificial intelligence.We present statistical and graphical results to illustrate the efficiency of our method.
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