Responsibility-aware Strategic Reasoning in Probabilistic Multi-Agent Systems

TL;DR

This paper introduces a new logic called PATL+R for strategic reasoning in probabilistic multi-agent systems that accounts for agents' causal responsibility, enabling balanced strategy synthesis with respect to responsibility and reward.

Contribution

It presents the logic PATL+R incorporating responsibility modalities and a method to compute responsibility-aware Nash equilibria through model checking, advancing responsible autonomous system design.

Findings

Developed the logic PATL+R with responsibility modalities.

Proposed a strategy synthesis approach balancing responsibility and reward.

Demonstrated computation of responsibility-aware Nash equilibria.

Abstract

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.