"Teammates, Am I Clear?": Analysing Legible Behaviours in Teams

TL;DR

This paper extends the concept of legible decision-making to multi-agent team settings, demonstrating that legible agents improve team performance in collaborative tasks.

Contribution

It introduces a novel extension of legible decision-making for multi-agent teams, enhancing collaboration and outperforming standard optimal agents.

Findings

Legible agents improve team performance in benchmark scenarios.

Teams with legible agents outperform teams with only standard agents.

The proposed method enhances collaboration in multi-agent systems.

Abstract

In this paper we investigate the notion of legibility in sequential decision-making in the context of teams and teamwork. There have been works that extend the notion of legibility to sequential decision making, for deterministic and for stochastic scenarios. However, these works focus on one agent interacting with one human, foregoing the benefits of having legible decision making in teams of agents or in team configurations with humans. In this work we propose an extension of legible decision-making to multi-agent settings that improves the performance of agents working in collaboration. We showcase the performance of legible decision making in team scenarios using our proposed extension in multi-agent benchmark scenarios. We show that a team with a legible agent is able to outperform a team composed solely of agents with standard optimal behaviour.