Resilience through adaptation

Authored by Arend Ligtenberg, Voorn George A K van, Broeke Guus A ten, Jaap Molenaar

Date Published: 2017

DOI: 10.1371/journal.pone.0171833

Sponsors: No sponsors listed

Platforms: NetLogo

Model Documentation: Other Narrative Flow charts Mathematical description

Model Code URLs: https://www.comses.net/codebases/5374/releases/1.0.0/

Abstract

Adaptation of agents through learning or evolution is an important component of the resilience of Complex Adaptive Systems (CAS). Without adaptation, the flexibility of such systems to cope with outside pressures would be much lower. To study the capabilities of CAS to adapt, social simulations with agent-based models (ABMs) provide a helpful tool. However, the value of ABMs for studying adaptation depends on the availability of methodologies for sensitivity analysis that can quantify resilience and adaptation in ABMs. In this paper we propose a sensitivity analysis methodology that is based on comparing time-dependent probability density functions of output of ABMs with and without agent adaptation. The differences between the probability density functions are quantified by the socalled earth-mover's distance. We use this sensitivity analysis methodology to quantify the probability of occurrence of critical transitions and other long-term effects of agent adaptation. To test the potential of this new approach, it is used to analyse the resilience of an ABM of adaptive agents competing for a common-pool resource. Adaptation is shown to contribute positively to the resilience of this ABM. If adaptation proceeds sufficiently fast, it may delay or avert the collapse of this system.

Tags

Agent-based model Simulation Complex adaptive systems emergence Norms Social-ecological systems perspective Sensitivity-analysis Distance Resource-management