# Value Alignment Equilibrium in Multiagent Systems

arXiv: https://arxiv.org/abs/2009.07619 · HTML: https://mlsanity.com/paper/2009.07619/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Human values and AI feedback alignment, one of 10 directions in LLM alignment / RLHF / preference optimisation.
- Builds on 0 of its 19 references that are in the map.
- First posted on arXiv 16 Sep 2020.

## Placed in

- LLM alignment / RLHF / preference optimisation / [Human values and AI feedback alignment](https://mlsanity.com/alignment/human-values-and-ai-feedback-alignment/)

## Abstract (arXiv)

Value alignment has emerged in recent years as a basic principle to produce beneficial and mindful Artificial Intelligence systems. It mainly states that autonomous entities should behave in a way that is aligned with our human values. In this work, we summarize a previously developed model that considers values as preferences over states of the world and defines alignment between the governing norms and the values. We provide a use-case for this framework with the Iterated Prisoner's Dilemma model, which we use to exemplify the definitions we review. We take advantage of this use-case to introduce new concepts to be integrated with the established framework: alignment equilibrium and Pareto optimal alignment. These are inspired on the classical Nash equilibrium and Pareto optimality, but are designed to account for any value we wish to model in the system.