Ultimate Ecology

Yannick Oswald, Thomas Schmickl
IEEE Symposium on Artificial Life (2017)

Abstract:

This  article  introduces  a  novel  approach  towards modeling evolutionary game-theoretical systems by creating a self-regulating  societal  ecosystem.  We  here  develop  a  very  simple model  of  a  cooperating  agent  population  that  interacts  with  a dynamically  changing  environment.  These  interaction  patterns are initially random but adapt with time in a process mimicking natural    adaptation    and    selection    in    biological    evolution: Ultimately,  a  homeostatic  system  emerges  from  scratch  that regulates the growth of populations and environmental resources in a sustainable way, exhibiting strong resilience to perturbations. Moreover, the agent population exhibits horizontal social behavior represented by the Ultimatum Game but also vertical evolution-
relevant  behavior  represented  by  reproductive  strategies.  The interplay between these horizontal and vertical mechanisms is in the focus of the analysis presented here. We found emergence of co-dependent   horizontal   and   vertical   norms.   Ultimately,   we analyzed the interplay between micro- and macro-properties and found  significant  effects,  suggesting  occurrence  of  emergence within the system: Micro properties are local and individual while macro properties are global and population-wide. We show that both levels interact and influence each other bilaterally as a result of the nonlinear and complex system behavior.