Crossing the chasm: a ‘tube-map’ for agent-based social simulation of policy scenarios in spatially-distributed systems

• DOI: 10.1007/s10707-018-00340-z
• Publication Date: 2019-01-08T11:08:51Z
• Authors: J. Gareth Polhill; Jiaqi Ge; Matthew P. Hare; Keith B. Matthews; Alessandro Gimona; Douglas Salt; Jagadeesh Yeluripati
• Keywords: Argument (complex analysis); Mainstream

Agent based models (ABMs) simulate actions and interactions of autonomous agents/groups their effect on systems as a whole, accounting for learning without assuming perfect rationality or complete knowledge. ABMs are an increasingly popular approach to studying complex, spatially distributed socio-environmental systems, but have still become established in the sense being one that is expected by those wanting explore scenarios such systems. Partly, this issue awareness – ABM new enough many people not heard it; partly, it confidence has more do prove itself if preferred method. This paper will identify advances craft deployment needed accepted part mainstream science policy stakeholders. The conduct has, over last decade, seen transition from using abstracted representations (supporting theory-led thought experiments) accessible derived empirically (to deliver applied analysis). enhanced perception potential users outputs latter salient credible. Empirical not, however, panacea, demands computing data resources, limiting applications domains where exist along with suitable environmental these required. Further, empirical facing serious questions validation ontology used describe system first place. Using Geoffrey A. Moore's Crossing Chasm lens, we argue way ahead lies identifying niches which can best demonstrate its advantages, working collaborators promises. leads us several areas work needed.