1) The document discusses using evolutionary knowledge discovery techniques to search for "phases" in the complex output of a simulation model of political behavior. 2) The model is run thousands of times with random parameter values to generate a large dataset that is then analyzed for patterns and clusters. 3) The goal is to identify simpler models or summaries of the complex model behavior that could aid in validating less complex models.

1. Searching for “Phases” in Evidence-Led Common-Sense Secondary Analysis of
Complex Simulation Specification Entities Simulation Output
Output using Evolutionary

Specification simulation rules and agent Comparison with evidence is facilitated if the The Model is run many times (in this case
Knowledge Discovery behaviour is informed by available entities in the simulation correspond to entities 7000 times) each time using randomly
Techniques evidence (as much as possible). Some that are observed in a naturalistic manner. selected parameter values (p1, p2,…). Many
examples are listed below. A Small District different measures are recorded concerning
Bruce Edmonds and other SCID the outcomes from different layers of the
Project Members Initial party preference inherited model (m1, m2, … including the predicted
Party preference can be linked to learning from variable, t). This provides a rich data set for
parents (e.g. Verba, Scholzman et al. 2005) . the secondary analysis.
Given that models that are adequate to
much social phenomena will necessarily be People vote out of habit
highly complex, we are left with the Going to the polls in one election will lead to a greater
likelihood of returning to the polls in a subsequent
necessity of understanding them. The election (e.g. Gerber, Green et al. 2003) .
approach here is to construct relevant but
complex simulation models to start with Voting is a social norm
(Data Integration Models) and then try and Civic duty is an important rationale for individual-level
turnout (e.g. Riker and Ordeshook, 1968).
model this with simpler models.
People share the political views of their greater This data is then distributed over a space
networks according to the values of a couple of the
Probability of agreement within a network depends on
the distribution of political opinion within one’s
parameters (the grey background patchwork
network (autoregressive networks) (e.g. Huckfeldt, indicates the density of this data in the space)
Johnson, and Sprague, 2004).
Emmigration Rate
Electors can be mobilised to vote by family,
friends and political parties
Household members, friends and political parties will
ask people to vote on election day (e.g. Cutts and
Fieldhouse, 2009).
A Household
There are high amounts of homophily in social
networks
Here, to aid in this search, we use Individuals have more contact with similar people (e.g.
evolutionary techniques to look for McPherson, Smith-Lovin et al. 2001).
hypotheses about the model behaviour, but
not over the whole parameter “space” but Education increases the level of political interest
The level of exposure to (political) information one is
rather to identify clusters where local exposed to increases when pursuing higher education
patterns hold – maybe akin to “phases” (e.g. Lewis-Beck, 2008).
Class
Activities
found in some physical systems. These Age
might suggest context-dependent rules for Political experts are more influential within
Ethnicity
Etc.
political discussion networks
a simpler model or summaries of the Level-of-Political-Interest
People will tend to listen to people they believe are
complex model behaviour to use in the political experts (those who have higher levels of
Memory
(relative) validation of simpler models. political interest/involvement) (e.g. Huckfeldt, 2001). Propensity for Moving Nearby
secondary is achieved using a locally
evaluated Genetic Programming algorithm Satisfaction with the outcome of an election
increases future turnout
which simultaneously develops arithmetic Positive reinforcement from voting will lead to further Discuss-politics-with person-23 blue expert=false
predictors of a target output (voter turnout) voting (e.g. Bendor, Diermeier and Ting, 2003) . neighbour-network year=10 month=3
and their scope. Lots-family-discussions year=10 month=2
Etc.
Voting can be hindered by personal shocks
The birth of a child disturbs habit (Plutzer, 2002). An Agent’s Memory of Events
Voting varies with age
What Next? The output (clusters and expressions) suggests hypotheses that can then: (a) be checked using specific simulation experiments and using
Declining health, mobility, and energy levels impede standard statistical tests (b) be explored in simpler and more abstract models (in particular to capture any significant “phase” changes that these
voting (e.g. Strate et al. 1989) indicate.