Self-complexification through integral feedback in eusocial paper wasps of various levels of sociality.

ABSTRACT: We investigate how simple physical interactions can generate remarkable diversity in the life history of social agents using data of social wasps, yielding complex scalable task partitioning. We built and analyzed a computational model to investigate how diverse task allocation patterns found in nature can emerge from the same behavioral blueprint. Self-organizing mechanisms of interwoven behavioral feedback loops, task-dependent time delays and simple material flows between interacting individuals yield an emergent homeostatic self-regulation while keeping the global colony performance scalable. Task allocation mechanisms based on implicitly honest signaling via material flows are not only very robust but are also highly evolvable due to their simplicity and reliability. We find that task

SUBMITTER: Schmickl T 

PROVIDER: S-EPMC10559818 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature