Colloquium

The meaning of resident’s opinions for spatial decision making; An agent-based simulation of continuous opinion dynamics under consideration of social and spatial influence

Organisator Laboratory of Geo-information Science and Remote Sensing
Datum

do 28 mei 2015 13:00 tot 13:30

Locatie Gaia, building number 101
Droevendaalsesteeg 3
101
6708 PB Wageningen
+31 317 48 16 00
Zaal/kamer 1

by Jan Neumann (Germany)

Abstract

This research deals with the implementation of the dynamics of opinions in a planning related agent-based model environment. The problem of current planning models is the ignoring of opinions as influencing factor on decision. Controversially however, current existing models for the simulation of opinion dynamics are ignoring a spatial component which is important for spatial planning models. Adding both, a spatial and social component to an dynamic model environment seemed a sensible approach to overcome this problem and to simulate opinions dynamics and learning capacity of agents. Therefore, it is investigated how the current role of opinions in multi-actor spatial planning could be simulated within an agentbased model environment and what this would add to our current understanding of dynamics in spatial planning. Literature review, conceptual model, ODD-protocol, and the implementation of the model on a certain case are methods that were used to answer the questions of this research. The results of the case study show, that multi-actor spatial planning’s models should consider a spatial component since it is an important influencing factor on the opinion of actors which are involved in decision making processes. The model could be used to highlight locations that are more or less conflicting according to actor’s opinions. Further, the model results showed adaptive-behaviour of actor’s opinions. The validation of the model results, however, remains problematic. A limited amount of components, the restriction to only several rules, and the absence of “reals” argumentation capacity provides model results that are far from a realistic outcome and therefore, hard to validate.