# Responsibility-aware Strategic Reasoning in Probabilistic Multi-Agent Systems

arXiv: https://arxiv.org/abs/2411.00146 · HTML: https://mlsanity.com/paper/2411.00146/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 36 references that are in the map.
- First posted on arXiv 31 Oct 2024.

## Builds on (most cited first, 8 of 8)

- [A Game-Theoretic Account of Responsibility Allocation](https://mlsanity.com/paper/2105.09129/) (2021)
- [Blameworthiness in Strategic Games](https://mlsanity.com/paper/1809.05485/) (2018)
- [Causality, Responsibility and Blame in Team Plans](https://mlsanity.com/paper/2005.10297/) (2020)
- [Equilibria-based Probabilistic Model Checking for Concurrent Stochastic Games](https://mlsanity.com/paper/1811.07145/) (2018)
- [Automatic Verification of Concurrent Stochastic Systems](https://mlsanity.com/paper/2008.04613/) (2020)
- [Learning Responsibility Allocations for Safe Human-Robot Interaction with Applications to Autonomous Driving](https://mlsanity.com/paper/2303.03504/) (2023)
- [Anticipating Responsibility in Multiagent Planning](https://mlsanity.com/paper/2307.16685/) (2023)
- [Formal Modelling of Safety Architecture for Responsibility-Aware Autonomous Vehicle via Event-B Refinement](https://mlsanity.com/paper/2401.04875/) (2024)

## Built on by (most cited first, 1 of 1)

- [Counterfactual Reasoning for Causal Responsibility Attribution in Probabilistic Multi-Agent Systems](https://mlsanity.com/paper/2605.13077/) (2026)

## Abstract (arXiv)

Responsibility plays a key role in the development and deployment of trustworthy autonomous systems. In this paper, we focus on the problem of strategic reasoning in probabilistic multi-agent systems with responsibility-aware agents. We introduce the logic PATL+R, a variant of Probabilistic Alternating-time Temporal Logic. The novelty of PATL+R lies in its incorporation of modalities for causal responsibility, providing a framework for responsibility-aware multi-agent strategic reasoning. We present an approach to synthesise joint strategies that satisfy an outcome specified in PATL+R, while optimising the share of expected causal responsibility and reward. This provides a notion of balanced distribution of responsibility and reward gain among agents. To this end, we utilise the Nash equilibrium as the solution concept for our strategic reasoning problem and demonstrate how to compute responsibility-aware Nash equilibrium strategies via a reduction to parametric model checking of concurrent stochastic multi-player games.