Cognitive Science and the New Testament A New Approach to Early Christian Research

(Axel Boer) #1

analyze texts as well as test hypothetical scenarios about historical processes.
Building on insights that we gained in former chapters about cultural learning
strategies and social network formation, in this chapter we experimented with
a simple, agent-based model in the NetLogo environment to study the spread
of the early Christian movement. We have seen that the outcomes depended
largely on the assumptions we built into the model. The agent-based model
offered room for experimenting with various aspects and details of the growth
of early Christianity that would have been extremely difficult or even impos-
sible to incorporate into the corresponding mathematical model of logistic
growth. Specifically, we tested how the use of different learning strategies
influenced the spread of the movement and what role missionaries (apostles)
could play under different circumstances. When we assumed low conversion
rates and concentrated on the early stage of the spread of the movement, the
role of the apostles proved to be especially significant.


APPENDIX

; (c) 2015 Istvan Czachesz
; NB wrapping has to be turned off in the World Settings tab!
breed [ apostles ] ;define“apostles”as a type of turtles
globals [ pagan-color follower-color apostle-color ] ; declaration of variables
used by several procedures
to setup ; execute these commands when the“setup”button is pushed
clear-all
resize-world -25 25 -25 25
set pagan-color white
set follower-color green
set apostle-color magenta
ask patches [ set pcolor pagan-color ]
ask patch 0 0 [ ; giving the message to the patch in the middle
set pcolor follower-color
]
reset-ticks
end
to go ; execute these commands when the“go”button is pushed
if ( apostles-number > 0 ) [ move-apostles ] ; if there are apostles, carry out
the“move-apostles”procedure (defined below)
update-patches ; carry out the“update-patches”procedure (defined below)
update-plot ; carry out the“update-plot”procedure (defined below)


Social Networks and Computer Models 203
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