Positive reinforcements help algorithm forecast underground natural reserves

Texas A&M University researchers have designed a reinforcement-based algorithm that automates the process of predicting the properties of the underground environment, facilitating the accurate forecasting of oil and gas reserves.

from News on Artificial Intelligence and Machine Learning https://ift.tt/3uq5He6
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