1. The Gaming of Policy and the Politics of Gaming
© Dr. Igor Mayer i.s.mayer@tudelft.nl
Faculty Technology, Policy and Management (TPM) & Signature Games
Delft University of technology, The Netherlands
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2. References
1. Mayer, I. S. (2009). The Gaming of Policy and the Politics of Gaming: A Review. Simulation & Gaming,
40(6), 825–862. doi:10.1177/1046878109346456
2. Mayer, I. S. (2008). Gaming for policy analysis: learning about complex multi-actor systems. In L. De
Caluwé, G. J. Hofstede, & V. Peters (Eds.), Why do games work? (pp. 31–40). Deventer: Kluwer.
3. Mayer, I. S., Bekebrede, G., Bilsen, A. van, Zhou, Q., & van Bilsen, A. (2009). Beyond Simcity: Urban
Gaming and Multi-Actor Systems. In E. Stolk & M. te Brommelstroet (Eds.), Model Town. Using Urban
Simulation in New Town Planning (pp. 168–181). Amsterdam: SUN/INTI.
4. Duffhues, J., Mayer, I. S., Nefs, M., & van der Vliet, M. (2013). Breaking Barriers to Transit-Oriented
Development: Insights from the Serious Game SPRINTCITY. Environment and Planning B (in press).
5. Mayer, I. S., Zhou, Q., Lo, J., Abspoel, L., Keijser, X., Olsen, E., … Kannen, A. (2013). Integrated,
Ecosystem-based Marine Spatial Planning: Design and Results of a Game-based Quasi-Experiment.
Ocean and Coastal Management, 82, 7–26. doi:dx.doi.org/10.1016/j.ocecoaman.2013.04.006
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3. Simulation-games
Simulation:
purposeful and valid/accurate, dynamic
representation of reality, formalized, often
quantitative, computerized, etc.
Game:
based upon a rule-set, imaginative, creative,
with social interaction (players), experiential,
immersion, engagement etc.
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4. Evolution
1890-1940
War gaming
1940s
Operations research
1950s
Systems Analysis
1960s
Policy analysis
• Krieg Spiel
• Ad hoc educational and
political games
• Science for decision making:
mathematics, economics,
engineering
• Optimization of Military
Logistics (raids, etc.)
• Game theory
• Operational gaming
• Think tanks
• Complex systems behavior by
looking at the entities.
• Formal Gaming (= simulation)
• 1st business games
• Cold war
• Social science perspective.
• Free form gaming
1970-80s
Social change and
critique
1980s-90s
Interactive policy
making
•Environment, 3rd world,
international relations crisis
•Crisis in planning and modeling
•System dynamics for
complexity
•Interactive, participatory
modeling and simulation
•Strengthening the policy maker
– modeler interface
2000s
Complexity
• Infrastructure planning
• Reinventing Serious gaming
for military, health care
• Net generation:
• Massive Multiplayer Online
Role Playing games
• Second Life, WoW, etc.
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Social networks and
mobility
•Game generation
•Internet / Mobile gaming
•Augmented and mixed reality
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5. Crisis in MSG for policy making (70s)
Many of the people in the US departments of Housing and Urban Development and Health, Education, and Welfare,
who are directly responsible for the millions of dollars that have gone into some of the public sector models,
simulations, and games, really could not care less what those MSGs produced as long as they, the research
sponsors, got credit for having been modern, management-oriented and scientific.
Brewer, 1975: 3
(…) close inspection (...) reveals a divergence of purpose between those who build and those who use MSGs having
a policy assisting intent; users are inadequately trained to know what they are buying from technical experts; and this
inadequacy also exists with respect to the experts knowing or caring about the users. What results are ill-developed
controls over the building and use of MSGs because (1) the actual users do not know how the information contained
in the model was generated; and (2) the experts responsible for the information contained in the model have
abnegated responsibility for the products through disinterest, contempt, and ignorance.
Brewer, 1975: iii
(...) none of the goals held out for large scale models have been achieved, and there is little reason to expect
anything different in the future (…) Methods for long range planning—whether they are called comprehensive
planning, large scale systems simulation, or something else—need to change drastically, if planners expect to have
any influence on the long run.
Lee, 1973: 16
(Gaming) is perhaps the ultimate comedown, as it means using the models as heuristic aids in the context of
operational gaming. Players make decisions in the synthetic city, observe the consequences and make new
decisions.
Lee, 1973: 25
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6. (Over)optimism of SG policy making?
Given the importance of models and
simulations in public policy making,
and the need to improve their
effectiveness, the governmental and
non-governmental model and
simulation building communities
should be striving to explore and build
on other existing model-building
practices. Some of the most
interesting work being done is within
the interactive entertainment industry.
Ben Sawyer, 2002:1
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7. Founding fathers of serious gaming
Johan Huizinga: ‗Homo Ludens‘ (1938)
Man is playful
Playing is stepping into a ‘magic circle’ (suspension of belief)
Culture emerges out of play(fulness)
Characteristics of play in judicial system, science, military, etc.
Johan Huizinga
Play is a serious matter (een ‘ernstige zaak’)
Caillois (1958)
Roger Cailliois
Clark Abt: ‗Serious games‘ (1968 / 1970)
War gaming for non-military purposes, like education and science
Clark Abt
Dick Duke: Gaming - the futures language (1974)
Increasing complexity of real world systems, policy making,
organizations and planning
Traditional communication cannot cope with complexity
New language = holistic / gestalt language
Gaming = holistic language of complexity.
Dick Duke
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8. Propositiona
1. A fairly simple game model can
communicate Real World complexity
2. While playing with a model,
students/professionals learn about the
Democracy 2
www.positech.co.uk/democracy2/
Player screen
Causal model
Energy Ville
underlying model of complexity!
3. Games are (represent) complex (multiactor) systems.
4. Through gaming we can learn to
understand (manage) a complex system.
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9. Complex multi actor systems
Energy
Water
Industry
Sea ports
Air ports
Rail
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10. Systems thinking:
The worldview of S&G
Factors:
Real world systems are based on many
variables that interact with each other in
dynamic feedback relations leading to
uncertainty (..) many variables can not be
quantified and there exists no proven
conceptual model or precedent to base
decision and action.
Actors:
The social political context (..) shows many
actors that may be strategic or a-rational
and finally there is a futures context in the
sense that the decision is irrevocable and
the results will not be understood well into
the future
Dick Duke, 1980
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12. Two forms of complexity
• Many interconnected and interdependent
technical-physical variables and systems.
•Incomplete information
•Uncertainty: cognitive, deep core, long
term
•Quantification problems
•Lack of proven scientific models
•Etc…
• Reductionist approach:
•Linear (steps, phases) or cyclical
(iterative) decision making
•Decision support & computer simulation
•Optimization, quantification
•Reduction, simplification, abstraction
•Etc.
Management
of technical
physical
complexity
Management
of social
political
complexity
•Stakeholder participation
•Process management
•Negotiated knowledge
•Soft tools – learning, persuasion.
Technical
physical
complexity
Social political
complexity
• Many interdependent, loosely coupled
stakeholders (policy network)
• Scientific disagreement and conflicts
• Disputed knowledge, values & norms
• Dynamic rounds and arena‘s (fluidity)
• Political compromises
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13. Combining technical and political
complexities
First, on the nature of the phenomena handled by planners, it is
increasingly recognized that the evolution of the urban
development process is an extraordinarily complex and dynamic
activity. In simple terms, it involves both physical and social
systems; here lies the heart of the problem, namely the
simultaneous handling of ―both types‖ of system as they evolve
and interact. On the one hand the physical system is relatively
simple to measure and represent as tangible elements are
involved. The components of the social system, on the other
hand, are not so convenient to handle, as volatile human
behavior is very much involved.
Taylor, 1971: 85
These two conventional methods can usefully address some
knowledge needs of global change issues, but are systematically
ill-equipped to address others. To address the knowledge needs
that are not well met by conventional methods, the paper argues
for the use of a set of alternative methods, known by various
names, including policy exercises, simulation gaming, and
scenario exercises.
Parson, 1997: 267
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14. E.g. Energy label for houses
Insulation
+
A
Energy consumption
-
B
-
-
+
-
D
A
C
B
C
+
+
-
F
E
Mental maps,
values, perceptions,.
interests, etc.
+
+
G
Mental maps,
values, perceptions,
interests, etc.
D
A
B
+
C
+
Mental maps,
values, perceptions,
interests, etc.
Mental maps,
values, perceptions,
interests, etc.
+
+
Mental maps,
values, perceptions,
interests, etc.
F
E
+
G
Mental maps,
values, perceptions,
interests, etc.
Mental maps,
values, perceptions,
interests, etc.
Mental maps,
values, perceptions
interests, etc.
Mental maps,
Values, perceptions,
interests, etc.
Mental maps,
values, perceptions,
interests, etc.
Mental maps,
values, perceptions,
interests, etc.
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15. Requirements for intervention tools
7. Authoritative.
• validity, reliability,
verification / justification,
falsification.
• timeliness, protecting
core values.
1. Integrative.
• Considers aspects,
levels, networks, sectors
disciplines in a holistic ,
integrative and systemic
way.
6. Communicative &
educational.
2. Dynamic.
• shows alternatives over time.
• Conveys meaning and
insights.
5. Flexible &
Reusable.
3. Interactive.
• Supports interaction,
negotiation among
multiple stakeholders.
• Adaptable, repeatable
for similar contexts;
modifiable to different
contexts.
4. Transparent.
• Not a black box for
stakeholders , but
insightful relations.
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