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Main Authors: Vishwanath, Ajay, Dennis, Louise A., Slavkovik, Marija
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2407.02425
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author Vishwanath, Ajay
Dennis, Louise A.
Slavkovik, Marija
author_facet Vishwanath, Ajay
Dennis, Louise A.
Slavkovik, Marija
contents Machine ethics is the field that studies how ethical behaviour can be accomplished by autonomous systems. While there exist some systematic reviews aiming to consolidate the state of the art in machine ethics prior to 2020, these tend to not include work that uses reinforcement learning agents as entities whose ethical behaviour is to be achieved. The reason for this is that only in the last years we have witnessed an increase in machine ethics studies within reinforcement learning. We present here a systematic review of reinforcement learning for machine ethics and machine ethics within reinforcement learning. Additionally, we highlight trends in terms of ethics specifications, components and frameworks of reinforcement learning, and environments used to result in ethical behaviour. Our systematic review aims to consolidate the work in machine ethics and reinforcement learning thus completing the gap in the state of the art machine ethics landscape
format Preprint
id arxiv_https___arxiv_org_abs_2407_02425
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Reinforcement Learning and Machine ethics:a systematic review
Vishwanath, Ajay
Dennis, Louise A.
Slavkovik, Marija
Artificial Intelligence
Machine ethics is the field that studies how ethical behaviour can be accomplished by autonomous systems. While there exist some systematic reviews aiming to consolidate the state of the art in machine ethics prior to 2020, these tend to not include work that uses reinforcement learning agents as entities whose ethical behaviour is to be achieved. The reason for this is that only in the last years we have witnessed an increase in machine ethics studies within reinforcement learning. We present here a systematic review of reinforcement learning for machine ethics and machine ethics within reinforcement learning. Additionally, we highlight trends in terms of ethics specifications, components and frameworks of reinforcement learning, and environments used to result in ethical behaviour. Our systematic review aims to consolidate the work in machine ethics and reinforcement learning thus completing the gap in the state of the art machine ethics landscape
title Reinforcement Learning and Machine ethics:a systematic review
topic Artificial Intelligence
url https://arxiv.org/abs/2407.02425