Demystifying emergent intelligence and its effect on performance in large robot swarms

John Harwell, London Lowmanstone, Maria Gini

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

1 Scopus citations

Abstract

We investigate the emergence of swarm intelligence using task allocation in large robot swarms. First, we compare task decomposition graphs of different levels of richness and measure the emergent intelligence arising from self-organized task allocation by deriving STOCH-N1, a stochastic allocation algorithm which contextualizes per-robot task allocation decisions based on a previous task's neighborhood within the graph. The results are compared to other state of the art algorithms. Second, we derive MAT-OPT: a greedy algorithm that optimally solves the swarm task allocation problem by representing the swarm's task allocation space as a matroid under some restrictive assumptions. We compare the MAT-OPT allocation method, which disregards task dependencies, with STOCH-N1, which emphasizes collective learning of graph structure (including dependencies). Results from an object gathering task show that swarm emergent intelligence (1) is sensitive to the richness of task decomposition graphs (2) is positively correlated with performance, (3) arises out of learning and exploitation of graph connectivity and structure, rather than graph content.

Original languageEnglish (US)
Title of host publicationProceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020
EditorsBo An, Amal El Fallah Seghrouchni, Gita Sukthankar
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages474-482
Number of pages9
ISBN (Electronic)9781450375184
StatePublished - 2020
Event19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020 - Virtual, Auckland, New Zealand
Duration: May 19 2020 → …

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume2020-May
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020
CountryNew Zealand
CityVirtual, Auckland
Period5/19/20 → …

Keywords

  • Foraging
  • Matroids
  • Swarm Robotics
  • Task Allocation
  • Task Decomposition

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