# Responsibility in a Multi-Value Strategic Setting

arXiv: https://arxiv.org/abs/2410.17229 · HTML: https://mlsanity.com/paper/2410.17229/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 29 references that are in the map.
- First posted on arXiv 22 Oct 2024.

## Builds on (most cited first, 4 of 4)

- [A Game-Theoretic Account of Responsibility Allocation](https://mlsanity.com/paper/2105.09129/) (2021)
- [Causality, Responsibility and Blame in Team Plans](https://mlsanity.com/paper/2005.10297/) (2020)
- [Anticipating Responsibility in Multiagent Planning](https://mlsanity.com/paper/2307.16685/) (2023)
- [Responsibility in Extensive Form Games](https://mlsanity.com/paper/2312.07637/) (2023)

## Abstract (arXiv)

Responsibility is a key notion in multi-agent systems and in creating safe, reliable and ethical AI. However, most previous work on responsibility has only considered responsibility for single outcomes. In this paper we present a model for responsibility attribution in a multi-agent, multi-value setting. We also expand our model to cover responsibility anticipation, demonstrating how considerations of responsibility can help an agent to select strategies that are in line with its values. In particular we show that non-dominated regret-minimising strategies reliably minimise an agent's expected degree of responsibility.