Why Reinforcement Learning in Energy Systems Needs Explanations

Fuente: arXiv
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Main Authors: Butt, Hallah Shahid, Schäfer, Benjamin
Format: Preprint
Published: 2024
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author Butt, Hallah Shahid
Schäfer, Benjamin
author_facet Butt, Hallah Shahid
Schäfer, Benjamin
contents With economic development, the complexity of infrastructure has increased drastically. Similarly, with the shift from fossil fuels to renewable sources of energy, there is a dire need for such systems that not only predict and forecast with accuracy but also help in understanding the process of predictions. Artificial intelligence and machine learning techniques have helped in finding out wellperforming solutions to different problems in the energy sector. However, the usage of state-of-the-art techniques like reinforcement learning is not surprisingly convincing. This paper discusses the application of reinforcement techniques in energy systems and how explanations of these models can be helpful
format Preprint
id arxiv_https___arxiv_org_abs_2405_18823
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Why Reinforcement Learning in Energy Systems Needs Explanations
Butt, Hallah Shahid
Schäfer, Benjamin
Artificial Intelligence
Systems and Control
With economic development, the complexity of infrastructure has increased drastically. Similarly, with the shift from fossil fuels to renewable sources of energy, there is a dire need for such systems that not only predict and forecast with accuracy but also help in understanding the process of predictions. Artificial intelligence and machine learning techniques have helped in finding out wellperforming solutions to different problems in the energy sector. However, the usage of state-of-the-art techniques like reinforcement learning is not surprisingly convincing. This paper discusses the application of reinforcement techniques in energy systems and how explanations of these models can be helpful
title Why Reinforcement Learning in Energy Systems Needs Explanations
topic Artificial Intelligence
Systems and Control
url https://arxiv.org/abs/2405.18823