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

作者：Beaulac Cedric; Larribe Fabrice

来源：International Journal of Computer Games Technology, 2017, 2017: 4939261.

DOI：10.1155/2017/4939261

<jats:p>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.</jats:p>

• 出版日期2017