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