Uncertain Machine Ethics Planning
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Abstract (arXiv)
Machine Ethics decisions should consider the implications of uncertainty over decisions. Decisions should be made over sequences of actions to reach preferable outcomes long term. The evaluation of outcomes, however, may invoke one or more moral theories, which might have conflicting judgements. Each theory will require differing representations of the ethical situation. For example, Utilitarianism measures numerical values, Deontology analyses duties, and Virtue Ethics emphasises moral character. While balancing potentially conflicting moral considerations, decisions may need to be made, for example, to achieve morally neutral goals with minimal costs. In this paper, we formalise the problem as a Multi-Moral Markov Decision Process and a Multi-Moral Stochastic Shortest Path Problem. We develop a heuristic algorithm based on Multi-Objective AO*, utilising Sven-Ove Hansson's Hypothetical Retrospection procedure for ethical reasoning under uncertainty. Our approach is validated by a case study from Machine Ethics literature: the problem of whether to steal insulin for someone who needs it.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 39 references that are in the map. First posted on arXiv 7 May 2025.
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2 of 39 references.
References · 2
- 2020Reinforcement Learning Under Moral Uncertaintycited by 16
- 2023Heuristic Search for Multi-Objective Probabilistic Planningcited by 4
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