Collective decision-making in multi-agent systems by implicit leadership

Chih Han Yu, Justin Werfel, Radhika Nagpal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

39 Scopus citations

Abstract

Coordination within decentralized agent groups frequently requires reaching global consensus, but typical hierarchical approaches to reaching such decisions can be complex, slow, and not fault-tolerant. By contrast, recent studies have shown that in decentralized animal groups, a few individuals without privileged roles can guide the entire group to collective consensus on matters like travel direction. Inspired by these findings, we propose an implicit leadership algorithm for distributed multi-agent systems, which we prove reliably allows all agents to agree on a decision that can be determined by one or a few better-informed agents, through purely local sensing and interaction. The approach generalizes work on distributed consensus to cases where agents have different confidence levels in their preferred states. We present cases where informed agents share a common goal or have conflicting goals, and show how the number of informed agents and their confidence levels affects the consensus process. We further present an extension that allows for fast decision-making in a rapidly changing environment. Finally, we show how the framework can be applied to a diverse variety of applications, including mobile robot exploration, sensor network clock synchronization, and shape formation in modular robots.

Original languageEnglish (US)
Title of host publication9th International Joint Conference on Autonomous Agents and Multiagent Systems 2010, AAMAS 2010
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1189-1196
Number of pages8
ISBN (Print)9781617387715
StatePublished - 2010
Externally publishedYes
Event9th International Joint Conference on Autonomous Agents and Multiagent Systems 2010, AAMAS 2010 - Toronto, ON, Canada
Duration: May 10 2010 → …

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume2
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference9th International Joint Conference on Autonomous Agents and Multiagent Systems 2010, AAMAS 2010
Country/TerritoryCanada
CityToronto, ON
Period5/10/10 → …

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Keywords

  • Biologically-inspired approaches and methods
  • Collective Intelligence
  • Distributed Problem Solving
  • Multi-robot systems

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