Agent-based models for first- and second-order emergent collective behaviours of social amoeba Dictyostelium discoideum aggregation and migration phases
Authored by Mohammad Parhizkar, Giovanna Di Marzo Serugendo
Date Published: 2018
DOI: 10.1007/s10015-018-0477-3
Sponsors:
Swiss National Science Foundation (SNSF)
Platforms:
MATLAB
Model Documentation:
Other Narrative
Flow charts
Model Code URLs:
Model code not found
Abstract
Collective behaviour in nature provides a source of inspiration for
engineering artificial systems (e.g. robotics, ecosystems of services),
due to their inherent mechanisms favouring adaptation to environmental
changes and enabling complex emergent behaviour to arise from a
relatively simple behaviour of individual entities. The first-order
emergence, also referred to as swarm intelligence, is well studied,
while higher order levels of emergent behaviour have not received much
attention yet. Second-order emergent behaviour arises from the
interactions of individuals, which are themselves the result of
first-order emergent behaviour. Dictyostelium discoideum provides a
compelling case for studying both first- and second-order emergence.
Individual cells move around on their own when there is plenty of food.
When food is scarce, cells self-aggregate towards a leading center cell
(first-order emergent behaviour) to build a super-organism, similar to a
slug. The slug displays properties that none of the cells has on its own
(e.g. sensitivity to light and heat). It moves as a whole (second-order
emergent behaviour) looking for a suitable place to transform into a
fruiting body (also known as sporocarp), where later the cells resume
their individual behaviour. This paper focuses specifically on the
aggregation and migration phases of Dictyostelium discoideum. We present
two agent-based models, implemented in Matlab for first order and Python
for second order. They display a series of emergent properties, among
others homogeneous aggregation territories size (first order) and
merging of slugs or new property as sensitivity to light (second order).
Future works involve implementing and experimenting both first- and
second-order emergence in swarm robotics, and identification of design
patterns for engineering higher order emergent behaviour in artificial
systems.
Tags
Multi-agent systems
differentiation
self-organisation
Quorum sensing
Cells
Cycle
Resistance
Gene
Binding
Mutants
Bio-inspired swarm modelling
Dictyostelium
discoideum
Higher order emergent
behaviour
Center initiation
Homolog