1 / 8

The Art of Social Simulation: Insights from Modelers and Case Studies

This document discusses the interactions between modelers and case-study teams, especially in the context of social simulation. It emphasizes the diversity of interaction patterns, the influence of distance and time, and the alignment of research agendas. Key suggestions for new modelers include being proactive in seeking qualitative data and understanding the importance of coding. The insights include Geller’s conjectures regarding the assumptions made in models. Furthermore, it advocates for improved training and protocol development to enhance collaboration in social simulation research.

haven
Télécharger la présentation

The Art of Social Simulation: Insights from Modelers and Case Studies

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Modelers are from Manchester; Case study teams are from Edinburgh Shah Jamal Alam University of Edinburgh

  2. The ‘Art’ of Social Simulation… “Science is what we understand well enough to explain to a computer. Art is everything else we do.” (Knuth, 1995) [Foreword in A=B]

  3. Some thoughts … 1 • Understanding modelers/case-study teams’ interaction • Many different patterns of interaction exist • Distance and time factors • Mode and frequency of interaction • Alignment of research agenda

  4. Some thoughts … 2 • Some suggestions for new modelers/PhD students • Be an extrovert modeler • A way to get qualitative data is by asking questions through a quick & dirty model • Be prepared to discard these prototype models • Do not try to build frameworks • Unless you have a job security

  5. Some thoughts … 3 • It’s the code, stupid • There’s a plenty of effort from conceptualization (diagrams etc.) to actual coding

  6. Geller’s first conjecture in Social Simulation*: • ‘The number of (informed) arbitrary assumptions (read magic numbers) introduced in a social simulation model due to limited evidence is proportional to the level of descriptiveness in the model.’ • Geller’s second conjecture in Social Simulation*: • ‘There is no way to avoid arbitrary assumptions in a reasonably descriptive social simulation model’ • * It’s a joke! Not to be attributed to any person (including Geller)

  7. Summarizing … • A working group to study different patterns of modelers/case-study teams interaction • Develop protocols • Training of students (e.g. ESSA school) • See Hare (2011; Env. Pol. Gov.); also, Polhill et al. (2010; JASSS) • Many reviewers are non-modelers or have stopped modeling • Seldom reviewers ask for a source code! • Document most assumptions in the model – especially, arbitrary assumptions • Is there enough description available to replicate a model? Code availability is essential!

  8. “Science advances whenever an Art becomes a Science. And the state of the Art advances too, because people always leap into new territory once they have understood more about the old.” (Knuth 1995) [Foreword in A=B]

More Related