Information Technology Reference
In-Depth Information
Just as with the CSNE analysis of natural language, this involves some
compromises. Using high-level structures in programming eases the task of program
construction, but it also can make the understanding and verification of code harder,
because the micro-level steps are not directly specified and the high-level structures
might encode assumptions that programmers do not fully understand. However, to a
large extent it should be the computer science that adapts to suit the kind of accounts
that people make of their behaviour rather than the other way around. Work is under
way to produce such architectures building on existing architectures (BDI) [14] and
past experience in developing architectures that suit the task of social simulation [7]
[13]. An early attempt to build-in context into an agent is in [6].
8
Concluding Discussion
The central claim of this paper is that a CSNE structure (or something similar) could
play a useful role in mediating between narrative data and the code that determines
agent behaviour within a simulation. Clearly however, there needs to be a synthesis
of methods to develop the most effective technique possible, drawing on a variety of
approaches, such as Grounded Theory [20], Conversational Analysis [15] or KnETs
[4]. This should be a creative and appropriate mix, which will not occur if each
approach holds inflexibly to its own traditions and shibboleths. The criteria for
judging any such method should be that it:
•
Preserves as much of the meaning in the original data as possible;
•
Introduces as few distortions as possible;
•
Is as transparent as possible, that is that when assumptions are used/added they are
clear from the report of the procedure and not implicit/hidden;
•
Is practical as a process and not demanding of impossible or infeasible steps;
•
Is as systematic as possible, so that others can attempt to retrace a reported analysis;
•
Is as honest as possible, in that it does not fudge results appearing to do more than it
can deliver.
A method that goes some way to meeting the above criteria could have a
transformative effect on social science in general by bringing together the worlds of
qualitative and quantitative evidence in a principled way via agent-based simulation.
Further enriching our simulations with information gained from narrative accounts
might change how agent-based social simulations look like, since they might include
some of the “mess” and complexity inherent in the social world we observed.
Acknowledgements.
This research was partially supported by the Engineering and
Physical Sciences Research Council, grant number EP/H02171X/1. Many thanks to
Emma Norling, Cathy Urquhart, Richard Taylor and all the participants of
the Informal Workshop on the topic held in Manchester (http://cfpm.org/
qual2rule/informal-workshop.html) with whom I have discussed these ideas.
