Abstract
One of the possible ways to embed values into autonomous agents is through reasoning over the norms that govern the MAS where agents are situated. Unfortunately, most previous research on value alignment of norms does not take into consideration the strong social dimension of values. Here, we take the stance that agents should be able to reason not exclusively about their own values, but also take into account the values that others in their community hold and how they interpret them. In this work, we present a novel functionality for autonomous agents to compute the perspective-dependent value alignment of norms. We build upon and integrate previous work on value representation, normative reasoning and Theory of Mind (the ability to perceive and interpret others in terms of their mental states, such as beliefs). This novel functionality enables an agent to compute the alignment of a set of norms with respect to a set of values not exclusively from its opinion perspective, but to switch its value structure and perception of the world at run-time using Theory of Mind, to estimate the alignment that another agent may have for the same set of norms. Our proposal opens new grounds for research on value-based negotiation over normative systems, where agents can perform better if they can estimate the opinion that their interlocutors have on the proposals they make.
Supported by the Spanish-funded VAE project (#TED2021-131295B-C31) and RYHMAS project (#PID2020-113594RB-100), the EU VALAWAI project (HORIZON #101070930), and the EU TAILOR project (H2020 #952215).
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Notes
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The clauses displayed in this section are written in Jason agent code. It follows a syntax very similar to that of Prolog, but using ampersand “ &” instead of comma for conjunction. Additionally, Jason built-in predicates are preceded by a dot “.”.
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Montes, N., Osman, N., Sierra, C. (2024). Perspective-Dependent Value Alignment of Norms. In: Osman, N., Steels, L. (eds) Value Engineering in Artificial Intelligence. VALE 2023. Lecture Notes in Computer Science(), vol 14520. Springer, Cham. https://doi.org/10.1007/978-3-031-58202-8_4
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