Fuel Prices Reinforcement Learning Environment
Published: 13 August 2024| Version 1 | DOI: 10.17632/wt5gd7jvm6.1
Contributor:
Richard Manu Nana Yaw Sarpong- StreetorDescription
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To create a universal model for forecasting petroleum fuel prices, researchers have turned to reinforcement learning as a promising method. This paper focuses on modeling the fuel price environment, a key component of reinforcement learning. The researchers have created a simulated environment using data from major crude oil markets worldwide, foreign exchange, and fuel prices. This model can be applied to the US market. The fuel price data and foreign exchange can be modified to reflect other geographic areas of study. You can find the Reinforcement Learning environment at https://github.com/rsarpongstreetor/DCE_Paper_for_rl_Env?tab=readme-ov-file#data_centric_engineering_paper_for_marl_env
Institutions
Universiti Teknologi PETRONAS
Categories
Arts and Humanities, Applied Sciences, Natural Sciences, Mathematics