<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.0 20120330//EN" "JATS-archivearticle1.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>A Policy Design Framework Using Agent-Based Social Simulations</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Alexander Melchior</string-name>
          <email>A.T.Melchior@uu.nl</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Department of Information and Computer Science, Utrecht University</institution>
        </aff>
      </contrib-group>
      <fpage>82</fpage>
      <lpage>90</lpage>
      <abstract>
        <p>In this paper we propose the development of a policy design framework using agent-based social simulations (ABSS). ABSS enable us to clearly articulate the problem(s) that we want to solve with policies and simulate the proposed policies to remedy the problem. One important aspect that we see in current policy development is the lack of awareness regarding context, perspective and bias. When a policy is developed, for instance, within one ministry it will usually have the context of that ministry, ignoring other perspectives in which the problem can be seen. This causes a (unintended) bias during the policy development and in the resulting policy. By creating an ABSS multiple contexts and perspective can be incorporated into one model to explicitly articulate these perspectives and biases. It also enables policy developers with expertise in a single context to add their insights to the model and see how this interacts with other contexts during the simulation. The emerging behavior in the ABSS gives insight in the di erent policy contexts. The proposed framework enables policy makers to match their policy problem with di erent ABSS design methods to see which best ts their needs. At the same time social simulation experts can gain more insight in the applicability of ABSS to policies.</p>
      </abstract>
      <kwd-group>
        <kwd>Policy development</kwd>
        <kwd>Social simulations</kwd>
        <kwd>Agent-based social simulations</kwd>
        <kwd>Emerging behaviour</kwd>
        <kwd>Simulation comparison</kwd>
        <kwd>Model</kwd>
        <kwd>Framework</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>
        Policy making, in all its forms, is extremely complex. This realization is
repeatedly discovered, something that was already pointed out a few decades ago
[
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. Developing policies is often done without clear goals, stakeholders, ideal
processes, (evaluation) metrics or open mindedness to new ways of working,
according to academics and governmental reports [
        <xref ref-type="bibr" rid="ref1 ref2 ref3">1,2,3</xref>
        ]. Not only is it complex,
it is also done in a dynamic world where political or societal surges in attention
can cause unexpected pivoting of the policy development direction. One way to
deal with this complexity is to use models in order to simplify problems, analyze
them and predict the e ect of policies. In the past decade more types of
models and approaches to policy making have become computational feasible, thus
giving us more options to deal with the policy design complexity.
      </p>
      <p>
        One of the new approaches that seems to be a promising way to deal with
the complexity is agent-based social simulation (ABSS) [
        <xref ref-type="bibr" rid="ref4 ref5 ref6 ref7 ref8 ref9">4,5,6,7,8,9</xref>
        ]. Creating
an ABSS enables us to articulate a problem, make it explicit and look at it from
many di erent angles. By doing so we expect to be able to improve the policy
making design process. The applicability of this idea is illustrated by di erent
examples [
        <xref ref-type="bibr" rid="ref10 ref11 ref12">10,11,12</xref>
        ] from di erent perspectives and disciplines.
      </p>
      <p>While we see the use of agent-based social simulations in these di erent
usecases we see no general approach for policy makers to use ABSS as design tool.
A framework that uses ABSS in a policy design process enables policy makers to
use this new approach in their work. The framework can also help the academic
research eld of social simulations, that is shared by many di erent disciplines, to
further the understanding of ABSS and their application to policy development.
This research project is sponsored by the Dutch Ministry of Economic A airs and
Climate Policy. As such we will focus on (socio-)economic and climate related
policy development.</p>
      <p>In this paper we will rst describe the problem more thoroughly, de ne the
problem domain and research eld. We will re ect on the state of the art and
the related literature. After this the research question and research method is
considered together with the means to accomplish our goals. We conclude with
the proposed approach for this research project and a short discussion on our
expected contribution.
2</p>
    </sec>
    <sec id="sec-2">
      <title>Problem Statement and Related Work</title>
      <p>In the introduction we touched upon the complexity of policy making and the
use of models to deal with this complexity. The ability to make models of reality
is very powerful as it enables us to come up with solutions for problems that
would otherwise be too complex or big to comprehend. But the use of models
not only brings us bliss, it has its limitations as well. Models are created in the
context of a perceived problem that manifests itself in reality; thus the model
has a perspective, a point of view, a bias, a context. While the initial creators
of the model mostly know the context of a model this context is often forgotten
or ignored by other users. Especially when a model seems to be working well in
the original context the attention for the context of the model is quickly lost.</p>
      <p>The importance of context is easy to overlook when using seemingly good
models, but will result in situations as shown in Fig.1. Here the initial model
is created to take di erent aspects of problem A into account such that the
generalizations in the model match the context of the problem. Once this model
produces good results other users adopt it for their own problems. Only a part of
the modeled aspects apply to problem B, resulting in a weak connection between
the model and reality.</p>
      <p>
        One of the reasons for this is the di culty in having a good insight in the
context, limitations and scope of a model. While policy development frameworks
like the Dutch integrated impact assessment framework (IAK) [
        <xref ref-type="bibr" rid="ref13">13</xref>
        ] are used in the
Netherlands to guide the general policy development process it is still hard to see
the actual problems deep down in the used models to make such assessments.
One could take the example of macro-economic models. These are based on
micro-economic models that are based on rational agents. Unfortunately the
core assumptions of rational agents can be questioned [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ].
      </p>
      <p>
        The existence and the challenge of this complex, context dependent, biased,
world of models is voiced by academics and policy makers more and more often
[
        <xref ref-type="bibr" rid="ref14 ref15 ref6 ref9">14,6,15,9</xref>
        ]. The current \state of the art" solution is the thought that more
research needs to be done in the area of using ABSS for policy development [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ].
      </p>
      <p>In ABSS one is able to explicitly model goals and means of agents,
representing humans. This could include interaction with other agents, changing
preferences of an agent, ways of reasoning of an agent and much more.
Depending on the context an agent can have di erent goals and means. This enables
policy makers to add elements to the simulation given their own context. Other
policy makers can add their insights, from a di erent context, to the same model.
When we run the simulation the interaction between the di erent contexts can
be analyzed by studing the agent`s behavior.
2.1</p>
      <sec id="sec-2-1">
        <title>Problem Domain, Research Field and Literature</title>
        <p>
          Problem domain: Policy development We de ne our problem domain as
\policy development", something that we have describe up to now as a complex
process. While policy development cycles and other approaches are de ned in
literature, real policy development isn't as nicely structured. Yet some trends are
visible despite the fact that each policy department (within Dutch ministries)
has its own way of making policies. One trend that we see is the increased focus
on quantitative analysis and evaluation, see [
          <xref ref-type="bibr" rid="ref16">16</xref>
          ] for an example from economics.
Designing an ABSS forces a policy developer to articulate the problem and
quantify it, thus improving the potential evaluation and the use of quantitative
data. Another trend is the digitalization of society and government.
        </p>
      </sec>
      <sec id="sec-2-2">
        <title>Research eld: The social simulation community The idea of using ABSS</title>
        <p>
          for policy development is not a new one, but there has been no structured work
on a general approach to use ABSS as a policy development tool. As such we
identify the need for a framework that uses ABSS as a policy development tool.
Others in the eld of ABSS have identi ed this need as well [
          <xref ref-type="bibr" rid="ref17">17</xref>
          ]. Just like policy
makers, the academics working with ABSS come from many di erent research
elds. They come from, and this is very limited set, elds like computer science,
economics, psychology, social science and philosophy. Each eld works in a very
di erent context and has di erent biases and goals. Yet all of them see ABSS
as a promising topic. A framework for using ABSS for policy development could
improve the understanding of other ABSS research and help the maturing of
this research eld.
        </p>
        <p>
          This is also represented in the literature that should give us a better
understanding of the current state of the art. As discussed the current status seems
to be that the need for research in this direction is needed [
          <xref ref-type="bibr" rid="ref4 ref7 ref9">4,7,9</xref>
          ] and
others are proposing similar approaches [
          <xref ref-type="bibr" rid="ref17">17</xref>
          ]. This could answer the need for new
ways towards policy development [
          <xref ref-type="bibr" rid="ref15 ref16 ref18 ref2">16,2,18,15</xref>
          ] Recent published works such as
\Simulating Social Complexity: A Handbook" [
          <xref ref-type="bibr" rid="ref19 ref6">19,6</xref>
          ] enables us to get quickly
acquainted with the current techniques. Modeling and context importance is
treated in [
          <xref ref-type="bibr" rid="ref14 ref20">20,14</xref>
          ] among others. Examples of ABSS like [
          <xref ref-type="bibr" rid="ref21">21</xref>
          ] can be further
studied as well.
3
        </p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>Research Question</title>
      <p>Our main goal is to build a framework for policy development using agent-based
social simulation design principles, this is re ected in RQ2. This framework will
require a way to compare possible solutions to be able to say something about
a proposed design, as stated in RQ3. Through answering RQ1 we will gain the
knowledge and tools needed to answer RQ2 and RQ3.</p>
      <p>In Section 4 we will use the research questions to formulate our proposed
approach for this research project in order to answer the research questions.
{ RQ1: What does the current policy design world look like? (Knowledge
problem)</p>
      <p>RQ1.1: How does the literature support the problem statement?
(Knowledge problem)
RQ1.2: What would the goal be of a policy design framework?
(Knowledge problem)
RQ1.3: Can we identify a useful use case for explorative work and
validation? (Knowledge problem)
{ RQ2: What does a framework for the design of agent-based social simulations
for policy development look like? (Design problem)</p>
      <p>RQ2.1: How can we characterize a problem that can be solved with
ABSS? (Design problem)
RQ2.2: How can we characterize a type of ABSS design? (Design
problem)
RQ2.3: Can we match the characteristics of a problem with the
characteristics of an ABSS in an e ective way? (Design problem)
{ RQ3: How can we compare ABSS's? (Design Problem)</p>
      <p>RQ3.1: How are ABSS evaluated? (Knowledge Problem)
RQ3.2: Is a general measure possible for the quality of an ABSS?
(Knowledge Problem)</p>
      <p>RQ3.3: Is a richer ABSS a better ABSS? (Knowledge Problem)
{ RQ4: Does the policy design framework improve the policy design process?
(Knowledge Problem)</p>
      <p>RQ4.1: What is the stakeholders' perception when using the policy design
framework? (Knowledge Problem)
RQ4.2: Are context, bias, and perspective made more explicit by using
the policy design framework? (Knowledge Problem)
RQ4.3: How do developed policies using the policy design framework
compare to other policies? (Knowledge Problem)</p>
      <p>Words such as e ective, measure, quality and richer are all representations
of the word utility. At this stage of the research project we know that these
words are not accurate enough but also regard a straightforward interpretation
far from trivial. Once we have a better understanding of the problem we will use
more appropriate terms for them.
3.1</p>
      <sec id="sec-3-1">
        <title>Research Method</title>
        <p>
          For this research we conduct a design science project [
          <xref ref-type="bibr" rid="ref22">22</xref>
          ]. As such the research
questions are categorized in knowledge questions (where we answer questions
by looking at artifacts in a problem context) and design questions (where one
designs an artifact to improve the problem context).
        </p>
        <p>The design science engineering cycle in Fig.2 guides us in placing our research
questions in the appropriate phases. We can place RQ1 and RQ3 in the problem
investigation, RQ2 and RQ3 in the Treatment design, RQ4 in the Treatment
validation phase. This guides us into the next Section (4) where we will discuss
the approach of this research project using the design cycle.
4</p>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>Proposed Approach and Preliminary Ideas</title>
      <p>Phase 1: Problem Investigation. In our stakeholder analysis we have
identied policy makers as main stakeholders. Their goal is to develop improved
policies in order to satisfy their own stakeholders, which can be numerous. At the
same time some of these stakeholders can be directly involved with this research
project: government management, operations management, policy implementers
or politicians.</p>
      <p>Another set of stakeholders are academics. They can further their insights
in the applicability of ABSS for policy development and the comparability of
ABSS.</p>
      <p>We rst plan to increase our understanding of the goals and needs of the
stakeholders with two courses of action. First we continue our literature research
on the following topics:
{ Policy development
{ Comparing problems and solutions
{ ABSS design
{ Framework design</p>
      <p>But literature can not teach us everything. Next to literature review we will
construct an ABSS toy case with Repast. This will be more informative as we
get to experience what it actually means to build an ABSS. This also means
that a deeper understanding of policy development is needed if we wish to apply
the ABSS to policy development.</p>
      <p>Phase 2: Treatment Design. During phase 1 of the research project we have
started with some requirement gathering by learning more about the problems
we face. We also expect to have learned more about the available treatments
that might be applicable to our problem statement and use these to create our
own policy design framework. The work in phase 1 will identify what the most
interesting initial approach will be for the creation of the framework, RQ2. While
working on RQ2 we will gather more information and insight for RQ3. RQ3 has
a major impact on the e ectiveness of the solutions made for RQ2.</p>
      <p>To make the requirements more concrete we will select a use case with policy
makers to use for the validation (phase 3).</p>
      <p>Phase 3: Treatment Validation. We will test and validate the framework
by designing a policy based on the use-case found during phase 1 and 2 using
the policy design framework. The resulting policy and design process will be
evaluated with the policy making stakeholders and will provide input for RQ4.
With this feedback we expect to be able to validate and improve the framework,
as a good design cycle would do. The questions posed in RQ4 are still imprecise,
we expect to learn what the important questions are during phase 1 and 2.</p>
      <p>We do like to note that the three phases are part of the engineering cycle,
as such we expect phase 3 to be input for a new phase 1 in this project and
continue to cycle through these phases.
4.1</p>
      <sec id="sec-4-1">
        <title>Preliminary Ideas</title>
        <p>Now that we have recounted our approach for this research project we can
discuss our preliminary ideas for a framework. In Fig.3 we can see a possible
representation of the characteristics of a problem (or policy) and an ABSS (design
process). Each of these have n aspects, approaches or characteristics that can be
matched. The aspects can be modeled using ontological modeling which gives
us a structured but exible way of modeling. Each of the ontologies has its own
context and creators, making it a social constructs. In the matching process we
can compare (RQ3) a match with other matches and select the matching set
that would be most useful for a problem.</p>
        <p>
          To compare matchings we can use approaches like TraceME [
          <xref ref-type="bibr" rid="ref23">23</xref>
          ] for
software comparisons ( -measurement). The analogy here is that both software
and policies describe rules and interactions, especially if we represent a policy
in an ABSS. With the TraceME approach we might also be able to answer RQ3
and its subquestions, but this is something we will discover during the research
project.
        </p>
        <p>
          For the use-case we are working with the ministry to nd an interesting topic
with a focus group. We will use an action research [
          <xref ref-type="bibr" rid="ref22 ref24">22,24</xref>
          ] approach for the
usecase. Once a use-case is found and the development of the ABSS has started
the plan is to work in a short cyclic manner to be able to adjust the direction
of development quickly. This short cyclic way of working might be one of the
aspects of the framework: if one nds a new aspect of the problem due to the
design work done on the ABSS it might be best to choose a di erent design
approach for this new problem aspect.
4.2
        </p>
      </sec>
      <sec id="sec-4-2">
        <title>Means</title>
        <p>In order to bring this research project to a successful end we have a number of
means that are available to us. A hybrid civic servant and PhD-researcher
position: my positions both at the Ministry of Economic A airs and Climate Policy
and Utrecht University enables us to easily use the networks of relevant experts
in both the policy development world and the academic world. Supervisor
expertise: the experience of Marcela Ruiz in -analysis and the expertise of Frank
Dignum in inter-disciplinary social simulations. Diverse personal background:
while my main background is in computer science I also have a background in
basic philosophy, social geography, urban planning and multiple advisory and
management roles. This mix matches the diversity of the ABSS and policy
design eld.
5</p>
      </sec>
    </sec>
    <sec id="sec-5">
      <title>Conclusion</title>
      <p>In this paper we have elaborated on our current understanding of one of the
problems at hand in the policy development world. ABSS seems to be well suited
to deal with context dependency issues of policy development and as such we
propose to use ABSS as a policy design framework. With this contribution we
expect to improve the policy development process and the quality of policies.
At the same time the framework can be used by other academics to gain more
insight in the applicability for policy development for their own work on ABSS.
This research project ts well in the current maturing process of the eld of
social simulations as it focuses on the applicability and takes a step back to look
at the eld of social simulations. I also like to thank my supervisors, Dr. Marcela
Ruiz and Dr. Frank Dignum, for their continued advice and expertise.</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          1.
          <string-name>
            <surname>Bovens</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Hart</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          : Understanding Policy Fiascoes. Transaction Publishers (
          <year>1998</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          2. Studiegroep Informatiesamenleving en Overheid:
          <article-title>Maak waar! (4</article-title>
          <year>2017</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          3.
          <string-name>
            <surname>Nowak</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kacprzyk-Murawska</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Serwotka</surname>
          </string-name>
          , E. In: Social Psychology and the Narrative Economy. Springer International Publishing,
          <string-name>
            <surname>Cham</surname>
          </string-name>
          (
          <year>2017</year>
          )
          <volume>45</volume>
          {
          <fpage>58</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          4.
          <string-name>
            <surname>Axelrod</surname>
          </string-name>
          , R.:
          <article-title>Advancing the art of simulation in the social sciences</article-title>
          . In Conte, R.,
          <string-name>
            <surname>Hegselmann</surname>
            ,
            <given-names>R.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Terna</surname>
          </string-name>
          , P., eds.: Simulating Social Phenomena, Berlin, Heidelberg, Springer Berlin Heidelberg (
          <year>1997</year>
          )
          <volume>21</volume>
          {
          <fpage>40</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          5.
          <string-name>
            <surname>Edmonds</surname>
            ,
            <given-names>B.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Gershenson</surname>
            ,
            <given-names>C.</given-names>
          </string-name>
          :
          <article-title>Modelling complexity for policy: Opportunities and challenges</article-title>
          .
          <source>CoRR abs/1310</source>
          .2290 (
          <year>2013</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          6.
          <string-name>
            <surname>Edmonds</surname>
          </string-name>
          , B., Meyer, R. In: Introduction. Springer International Publishing,
          <string-name>
            <surname>Cham</surname>
          </string-name>
          (
          <year>2017</year>
          )
          <volume>3</volume>
          {
          <fpage>12</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          7.
          <string-name>
            <surname>Gilbert</surname>
            ,
            <given-names>N.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Ahrweiler</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Barbrook-Johnson</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Narasimhan</surname>
            ,
            <given-names>K.P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Wilkinson</surname>
          </string-name>
          , H.:
          <article-title>Computational modelling of public policy: Re ections on practice</article-title>
          .
          <source>Journal of Arti cial Societies and Social Simulation</source>
          <volume>21</volume>
          (
          <issue>1</issue>
          ) (
          <year>2018</year>
          )
          <fpage>14</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          8.
          <string-name>
            <surname>Ormerod</surname>
          </string-name>
          , P. In: Economics. Springer International Publishing,
          <string-name>
            <surname>Cham</surname>
          </string-name>
          (
          <year>2017</year>
          )
          <volume>19</volume>
          {
          <fpage>44</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          9.
          <string-name>
            <surname>Rosewell</surname>
          </string-name>
          , B.
          <source>In: Complexity Science and the Art of Policy Making</source>
          . Springer International Publishing,
          <string-name>
            <surname>Cham</surname>
          </string-name>
          (
          <year>2017</year>
          )
          <volume>159</volume>
          {
          <fpage>178</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          10.
          <string-name>
            <surname>Ghorbani</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Dechesne</surname>
            ,
            <given-names>F.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Dignum</surname>
            ,
            <given-names>V.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Jonker</surname>
            ,
            <given-names>C.</given-names>
          </string-name>
          :
          <article-title>Enhancing abm into an inevitable tool for policy analysis</article-title>
          .
          <source>Policy and Complex Systems</source>
          <volume>1</volume>
          (
          <issue>1</issue>
          ) (
          <year>2014</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          11.
          <string-name>
            <surname>Maglio</surname>
            ,
            <given-names>P.P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Cefkin</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Haas</surname>
            ,
            <given-names>P.J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Selinger</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          :
          <article-title>Social factors in creating an integrated capability for health system modeling and simulation</article-title>
          . In Chai,
          <string-name>
            <given-names>S.K.</given-names>
            ,
            <surname>Salerno</surname>
          </string-name>
          ,
          <string-name>
            <given-names>J.J.</given-names>
            ,
            <surname>Mabry</surname>
          </string-name>
          , P.L., eds.
          <source>: Advances in Social Computing</source>
          , Berlin, Heidelberg, Springer Berlin Heidelberg (
          <year>2010</year>
          )
          <volume>44</volume>
          {
          <fpage>51</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          12.
          <string-name>
            <surname>Montanola-Sales</surname>
            ,
            <given-names>C.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Onggo</surname>
            ,
            <given-names>B.S.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Casanovas-Garcia</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          :
          <article-title>Agent-based simulation validation: A case study in demographic simulation</article-title>
          .
          <source>In: Proceedings of the Third International Conference on Advances in System Simulation (SIMUL</source>
          <year>2011</year>
          ).
          <article-title>(</article-title>
          <year>2011</year>
          )
          <volume>109</volume>
          {
          <fpage>115</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref13">
        <mixed-citation>
          13.
          <article-title>Dutch Ministry of Justice and Security: The integrated impact assessment framework for policy and legislation (</article-title>
          <year>12 2016</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref14">
        <mixed-citation>
          14.
          <string-name>
            <surname>Edmonds</surname>
            ,
            <given-names>B.</given-names>
          </string-name>
          <article-title>In: The Room Around the Elephant: Tackling Context-Dependency in the Social Sciences</article-title>
          . Springer International Publishing,
          <string-name>
            <surname>Cham</surname>
          </string-name>
          (
          <year>2017</year>
          )
          <volume>195</volume>
          {
          <fpage>208</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref15">
        <mixed-citation>
          15.
          <string-name>
            <surname>Houppermans</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          : Twee Kanten van de Medaille: een onderzoek naar de kwaliteit van de beleidsvoorbereiding.
          <source>PhD thesis</source>
          , U (
          <year>September 2011</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref16">
        <mixed-citation>
          16. Expertwerkgroep E ectmeting:
          <article-title>Durf te meten - eindrapport expertwerkgroep effectmeting (11</article-title>
          <year>2012</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref17">
        <mixed-citation>
          17.
          <string-name>
            <surname>Perello-Moragues</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Noriega</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          :
          <article-title>Using agent-based simulation to understand the role of values in policy-making</article-title>
          .
          <source>SSC 2018 Conference</source>
          , Stockholm (8
          <year>2018</year>
          )
          <article-title>Used rst submitted version.</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref18">
        <mixed-citation>
          18.
          <string-name>
            <surname>Gilbert</surname>
            ,
            <given-names>N.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Terna</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          :
          <article-title>How to build and use agent-based models in social science</article-title>
          .
          <source>Mind &amp; Society</source>
          <volume>1</volume>
          (
          <issue>1</issue>
          ) (
          <year>Mar 2000</year>
          )
          <volume>57</volume>
          {
          <fpage>72</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref19">
        <mixed-citation>
          19.
          <string-name>
            <surname>Edmonds</surname>
          </string-name>
          , B. In: Di erent Modelling Purposes. Springer International Publishing,
          <string-name>
            <surname>Cham</surname>
          </string-name>
          (
          <year>2017</year>
          )
          <volume>39</volume>
          {
          <fpage>58</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref20">
        <mixed-citation>
          20.
          <string-name>
            <surname>Edmonds</surname>
            ,
            <given-names>B.</given-names>
          </string-name>
          :
          <article-title>The use of models - making mabs more informative</article-title>
          . In Moss, S.,
          <string-name>
            <surname>Davidsson</surname>
          </string-name>
          , P., eds.:
          <string-name>
            <surname>Multi-Agent-Based</surname>
            <given-names>Simulation</given-names>
          </string-name>
          , Berlin, Heidelberg, Springer Berlin Heidelberg (
          <year>2001</year>
          )
          <volume>15</volume>
          {
          <fpage>32</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref21">
        <mixed-citation>
          21.
          <string-name>
            <surname>Ahrweiler</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          :
          <article-title>Agent-based simulation for science, technology, and innovation policy</article-title>
          .
          <source>Scientometrics</source>
          <volume>110</volume>
          (
          <issue>1</issue>
          ) (
          <year>Jan 2017</year>
          )
          <volume>391</volume>
          {
          <fpage>415</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref22">
        <mixed-citation>
          22.
          <string-name>
            <surname>Wieringa</surname>
          </string-name>
          , R.:
          <article-title>Design science methodology for information systems</article-title>
          and software engineering. Springer (
          <year>2014</year>
          )
          <volume>10</volume>
          .1007/978-3-
          <fpage>662</fpage>
          -43839-8.
        </mixed-citation>
      </ref>
      <ref id="ref23">
        <mixed-citation>
          23.
          <string-name>
            <surname>Carmona</surname>
            ,
            <given-names>L.M.R.:</given-names>
          </string-name>
          <article-title>TraceME: Traceability-based Method for Conceptual Model Evolution</article-title>
          .
          <source>PhD thesis</source>
          , Universitat Politecnica de Valencia (
          <year>2016</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref24">
        <mixed-citation>
          24.
          <string-name>
            <surname>Davison</surname>
            ,
            <given-names>R.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Martinsons</surname>
            ,
            <given-names>M.G.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kock</surname>
          </string-name>
          , N.:
          <article-title>Principles of canonical action research</article-title>
          .
          <source>Information systems journal 14(1)</source>
          (
          <year>2004</year>
          )
          <volume>65</volume>
          {
          <fpage>86</fpage>
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>