Value-alignment in normative multi-agent systems is used to promote a certain value and to ensure the consistent behaviour of agents in autonomous intelligent systems with human values. However, the current literature is limited to the incorporation of effective norms for single-value alignment with no consideration of agents' heterogeneity and the requirement of simultaneous promotion and alignment of multiple values. This research proposes a multi-value promotion model that uses multi-objective evolutionary algorithms and decentralised reasoning to produce the optimum parametric set of norms that is aligned with multiple simultaneous values of heterogeneous agents and the system. To understand various aspects of this complex problem, several evolutionary algorithms were used to find a set of optimised norm parameters considering two toy tax scenarios with two and five values are considered. The results are analysed from different perspectives to show the impact of a selected evolutionary algorithm on the solution, and the importance of understanding the relation between values when prioritising them.

翻译：规范多智能体系统中的价值对齐用于促进特定价值，并确保自主智能系统中智能体行为与人类价值观一致。然而，现有文献仅限于针对单一价值对齐的有效规范整合，未考虑智能体的异质性以及同时促进和对齐多个价值的需求。本研究提出一种多价值促进模型，利用多目标进化算法和分散式推理，生成与异质性智能体及系统的多种同步价值对齐的最优规范参数集。为探究这一复杂问题的不同层面，本研究采用多种进化算法，在考虑两种及五种价值的两个玩具税收场景中寻找优化的规范参数集。通过从不同角度分析结果，展示所选进化算法对解决方案的影响，并阐明在价值优先级排序时理解价值间关系的重要性。