Applications and design of cooperative multi-agent ARN-based systems

Claire E. Gerrard*, John McCall, Christopher Macleod, George M. Coghill

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

The Artificial Reaction Network (ARN) is an artificial chemistry inspired by Cell Signalling Networks. Its purpose is to represent chemical circuitry and to explore the computational properties responsible for generating emergent high-level behaviour. In this paper, the design and application of ARN-based cell-like agents termed “Cytobots” are explored. Such agents provide a facility to explore the dynamics and emergent properties of multicellular systems. The Cytobot ARN is constructed by combining functional motifs found in real biochemical networks. By instantiating this ARN, multiple Cytobots are created, each of which is capable of recognising environmental patterns, stigmergic communication with others and controlling its own trajectory. Applications in biological simulation and robotics are investigated by first applying the agents to model the life-cycle phases of the cellular slime mould D. discoideum and then to simulate an oil-spill clean-up operation. The results demonstrate that an ARN-based approach provides a powerful tool for modelling multi-agent biological systems and also has application in swarm robotics.

Original languageEnglish
Pages (from-to)1581-1594
Number of pages14
JournalSoft Computing
Volume19
Issue number6
Early online date21 Jun 2014
DOIs
Publication statusPublished - Jun 2015

Keywords

  • Artificial Chemistry
  • Artificial Neural Network (ANN)
  • Artificial Reaction Network (ARN)
  • Swarm Robotics

ASJC Scopus subject areas

  • Software
  • Geometry and Topology
  • Theoretical Computer Science

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