Quorum sensing without deliberation: biological inspiration for externalizing computation to physical spaces in multi-robot systems

Theodore Pavlic, Jake Hanson, Gabriele Valentini, Sara Imari Walker, Stephen C. Pratt

Research output: Contribution to journalArticlepeer-review

Abstract

Quorum sensing (QS) is ubiquitous in distributed, multi-agent systems in nature—from bacteria to arthropods to primates—and has been proposed as a useful distributed algorithm in engineered systems—from multi-robot systems to Internet server farms. Achieving QS requires groups to collectively integrate information about their numbers and reach consensus on an action contingent upon those numbers. In nest-site selection tasks that employ QS in ants, sensitivity to encounter rate has been implicated as a mechanism for how individuals sense that quorum has been reached. However, little is known about how individual ants estimate proximity to the critical rate. Ant-inspired QS algorithms proposed by computer scientists either heavily depend on communication between agents or the ability for individual agents to accumulate information over many encounters with others. Both communication and significant memory storage may be beyond the simple capabilities of small-scale robots in large collectives. Alternatively, if cognition was embodied across the group of agents and their physical environment, cognitive abilities could far exceed the abilities of each individual. Toward this end, we propose a novel bio-inspired algorithm for QS on mobile agents within a confined space. Our approach does not require individuals to communicate or count over long sequences of encounters; instead, QS emerges from the random interaction of mobile excitable agents with each other and the physical cavity. We validate theoretical predictions for our algorithm’s performance in simulation, and we also show that it has good qualitative agreement with accuracy and response-time data from real ants. More broadly, our algorithm provides a new, concrete example of how ants can serve as conceptual models for hypothetical dynamic networks of mobile neurons.

Original languageEnglish (US)
JournalSwarm Intelligence
DOIs
StateAccepted/In press - 2021

Keywords

  • Bio-inspired
  • Cognition
  • Collective decision making
  • Distributed robot systems
  • Multi-agent systems
  • Multi-robot systems
  • Quorum sensing
  • Swarms

ASJC Scopus subject areas

  • Artificial Intelligence

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