SwarmPlay: Interactive Tic-tac-toe Board Game with Swarm of Nano-UAVs driven by Reinforcement Learning

TL;DR

SwarmPlay introduces an interactive Tic-tac-toe game where a swarm of nano-UAVs uses reinforcement learning to engage humans, enhancing interactivity and engagement beyond traditional AI game systems.

Contribution

The paper presents a novel RL-based multi-agent drone swarm for interactive gameplay, demonstrating increased user engagement and interaction compared to traditional AI methods.

Findings

Participants highly engaged with drone swarm (70% maximum Likert score)

Users found the drone game less artificial than computer-based systems (80%)

SwarmPlay shows potential for wider application in interactive gaming

Abstract

Reinforcement learning (RL) methods have been actively applied in the field of robotics, allowing the system itself to find a solution for a task otherwise requiring a complex decision-making algorithm. In this paper, we present a novel RL-based Tic-tac-toe scenario, i.e. SwarmPlay, where each playing component is presented by an individual drone that has its own mobility and swarm intelligence to win against a human player. Thus, the combination of challenging swarm strategy and human-drone collaboration aims to make the games with machines tangible and interactive. Although some research on AI for board games already exists, e.g., chess, the SwarmPlay technology has the potential to offer much more engagement and interaction with the user as it proposes a multi-agent swarm instead of a single interactive robot. We explore user's evaluation of RL-based swarm behavior in comparison with the game theory-based behavior. The preliminary user study revealed that participants were highly engaged in the game with drones (70% put a maximum score on the Likert scale) and found it less artificial compared to the regular computer-based systems (80%). The affection of the user's game perception from its outcome was analyzed and put under discussion. User study revealed that SwarmPlay has the potential to be implemented in a wider range of games, significantly improving human-drone interactivity.