Multi-agent Coordination Under Temporal Logic Tasks and Team-Wise Intermittent Communication

TL;DR

This paper introduces an online decentralized coordination method for multi-agent systems that optimizes local task execution and communication timing under intermittent communication constraints, improving flexibility and efficiency.

Contribution

It proposes a novel decentralized potential game approach allowing agents to dynamically join or leave communication networks, optimizing both local plans and communication strategies.

Findings

Achieves guaranteed local task completion under intermittent communication.

Outperforms baseline methods in numerical simulations.

Provides a scalable decentralized coordination framework.

Abstract

Multi-agent systems outperform single agent in complex collaborative tasks. However, in large-scale scenarios, ensuring timely information exchange during decentralized task execution remains a challenge. This work presents an online decentralized coordination scheme for multi-agent systems under complex local tasks and intermittent communication constraints. Unlike existing strategies that enforce all-time or intermittent connectivity, our approach allows agents to join or leave communication networks at aperiodic intervals, as deemed optimal by their online task execution. This scheme concurrently determines local plans and refines the communication strategy, i.e., where and when to communicate as a team. A decentralized potential game is modeled among agents, for which a Nash equilibrium is generated iteratively through online local search. It guarantees local task completion and intermittent communication constraints. Extensive numerical simulations are conducted against several strong baselines.