Behaviour Space: Simulating Roman Social Life and Civil Violence

Shawn Graham

doi:10.16995/dscn.109

Abstract

Agent based modelling, also known as individual-based modelling, holds great promise for historians as a tool for formalizing and visualizing historians’ understandings of historical processes. It also provides a means to explore exploring the emergent consequences of such assumptions. Such models specify the possible behaviours for a single individual, and then enable individuals within the simulation to interact, with each applying the behaviours in a context-specific manner. Artificial societies begin to emerge from these interactions, allowing us to study their characteristics. Moreover, when these models produce behaviours that cohere with patterns embedded in historical or archaeological data, it becomes possible to interrogate aspects of past experience otherwise lost to us. This article presents PatronWorld, an agent based model of the ancient Roman daily ritual of salutatio, a ritual in which clients gathered to make a morning greeting to their patron. It explores the ritual’s role in the development and maintenance of patronage networks, and its relationship to the emergence of civil violence in the Roman world. The model is also based on a framework that describes the social network surrounding land holding (the foundations of wealth in antiquity) in the City of Rome from the late first – early second century AD. Civil violence was a constant feature of Roman society, frequently targeting the men upon whose social connections the political economy of the state depended. Results from the model suggest the social conditions that made the state vulnerable to periodic bouts of violence, and suggest new directions for further research.

Highlights

Crowds are a part of our everyday lives
The static floor field was initialized according to the linear distance between the centre of each cell and the centre of the exit cell
Revision of Kirchner’s cell-selection function by introducing a value of kn = 0.5 significantly decreased the number of agents remaining after a fixed time compared to other values of kn. This is because the revised cell-selection rule no longer requires that occupied cells spend a time step unoccupied. Since this rule applies to the exit cell as well, the original model’s maximum exit rate was one agent per two time steps, while the new rule allows for a maximum exit rate of one agent per time step

Summary

Introduction

Crowds are a part of our everyday lives. While most crowds are safe, some can be dangerous: this year alone over 250 pilgrims were crushed during the Hajj, and over 80 were crushed at the lantern festival in Beijing. Crowd events are interesting to social simulation researchers because their associated phenomena are largely emergent in nature. Crowds demonstrate speed and force-related effects, including rainbow-like arching structures as pedestrians jam and clog at exits, bursty exit rates as jostling prevents smooth use of doors, and inability for crowds to pass through each other when speeds (and forces) are high [1]. All these crowd effects are generally observable from an overhead perspective, and we are all aware from our personal experience that individual pedestrians do not plan them

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