Artificial virtuous agents in a multiagent tragedy of the commons
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Abstract (arXiv)
Although virtue ethics has repeatedly been proposed as a suitable framework for the development of artificial moral agents (AMAs), it has been proven difficult to approach from a computational perspective. In this work, we present the first technical implementation of artificial virtuous agents (AVAs) in moral simulations. First, we review previous conceptual and technical work in artificial virtue ethics and describe a functionalistic path to AVAs based on dispositional virtues, bottom-up learning, and top-down eudaimonic reward. We then provide the details of a technical implementation in a moral simulation based on a tragedy of the commons scenario. The experimental results show how the AVAs learn to tackle cooperation problems while exhibiting core features of their theoretical counterpart, including moral character, dispositional virtues, learning from experience, and the pursuit of eudaimonia. Ultimately, we argue that virtue ethics provides a compelling path toward morally excellent machines and that our work provides an important starting point for such endeavors.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 12 of its 99 references that are in the map. First posted on arXiv 6 Oct 2022.
Builds on
12 of 99 references.
References · 12
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Built on by
Citing papers per year: 2023: 1; 2024: 1; 2025: 0; 2026: 1.
3 papers.
- 2024Reinforcement Learning and Machine ethics:a systematic reviewcited by 3
- 2023On the Computational Complexity of Ethics: Moral Tractability for Minds and Machinescited by 2
- 2026Fog of Love: Engineering Virtuous Agent Behavior with Affinity-based Reinforcement Learning in a Game Environmentcited by 0
- 2026Fog of Love: Engineering Virtuous Agent Behavior with Affinity-based Reinforcement Learning in a Game Environment3 Jun 2026
- 2024Reinforcement Learning and Machine ethics:a systematic review2 Jul 2024
- 2023On the Computational Complexity of Ethics: Moral Tractability for Minds and Machines8 Feb 2023