Abstract

This paper investigates how political decisions emerge from complex, multi-actor governance environments using an agent-based modelling (ABM) framework. Building on a multi-layered urban climate governance model developed for the municipality of Askøy, Norway, we isolate and systematically analyse the political decision-making component of the process. The model integrates signals from urban planners, societal feedback, non-governmental organizations (NGOs), and media, which are aggregated by heterogeneous political agents through a two-stage process combining utility-based evaluation and peer influence dynamics. Through controlled simulation experiments, we examine how decision outcomes (acceptance, rejection, or revision) depend on factors such as signal configurations, decision thresholds, and party affiliation. Results reveal that decision dynamics are highly non-linear, characterized by tipping points and regime shifts rather than simple additive effects of inputs. While external signals largely determine outcomes under aligned conditions, internal political factors (such as party alignment, individual preferences, and strategic orientation) become critical in scenarios with high conflict. The findings provide a structured understanding of the aggregation mechanisms linking various input signals to political outcomes.

Önder Gürcan

Senior Researcher

My research interests include multi-agent systems, collective intelligence, self-organization and self-adaptation, simulation of biological systems, distributed clock synchronization and behavioural economics.