An introduction to the technique with two example models of in-group bias and voter turnout. An invited talk at the BIGSSS Summer Schools in Computational Social Science, at the Jacobs Bremen University, July 2018.

1. An Introduction to Agent-Based
Modelling
Bruce Edmonds
Centre for Policy Modelling
Manchester Metropolitan University

2. Introduction
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 2

3. An Example: Social Norms
• A social norm emerges partly as a result of the
beliefs, self-identity, actions, etc. of individuals
• But, simultaneously, the same norm
constrains/influences the perceptions, beliefs, self-
identity, actions, etc. of those individuals
• What we identify and label as a “social norm” is a
dynamic complex of upwards “emergence” and
downwards “immergence”
• Like many social phenomena, it has a complex
micro-macro relationship/interaction at its core
• Agent-based simulation allows the representation
and exploration of such micro-macro complexes
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 3

4. Micro-Macro Relationships
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 4

5. Introduction to Method
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 5

6. Analytic models
Where the model is expressed in terms that
allow for formal inferences about its
general properties to be made
• e.g. Mathematical formulae
• Where you don’t have to compute the
consequences but can derive them logically
• Usually requires numerical representation of
what is observed (but not always)
Only fairly “simple” mathematical models can be
treated analytically – the rest have to be
simulated/calculated
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 6

7. Equation-based/statistical/system
dynamics modelling
Observed World Equation-based Model
Outcomes
Aggregated
Outcomes
Aggregated
Model Outcomes
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 7

8. Computational models
Where a process is modelled in a series of
precise instructions (the program) that
can be “run” on a computer
• The same program always produces the
same results (essentially) but...
• ...may use a “random seed” to randomise
certain aspects
• Can be simple or very complex
• Often tries to capture more “qualitative”
aspects of social phenomena
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 8

9. Individual-based simulation
Observed World Computational Model
Outcomes Model Outcomes
Aggregated
Outcomes
Aggregated
Model Outcomes
Agent-
What is Agent-Based Social Simulation? By Bruce Edmonds, @Methods@Manchester, April 7th
2011, slide 9

10. Characteristics of agent-based
modelling
• Computational description of process
• Not usually analytically tractable
• More context-dependent…
• … but assumptions are much less drastic
• Detail of unfolding processes accessible
– more criticisable (including by non-experts)
• Used to explore inherent possibilities
• Validatable by data, opinion, narrative ...
• Often very complex themselves
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 10

11. What happens in ABSS
• Entities in simulation are decided up
• Behavioural Rules for each agent specified (e.g. sets of
rules like: if this has happened then do this)
• Repeatedly evaluated in parallel to see what happens
• Outcomes are inspected, graphed, pictured, measured
and interpreted in different ways
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 11
Simulation
Representations of OutcomesSpecification (incl. rules)

12. Example 1: Schelling’s Segregation
Model
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 12
Schelling, Thomas C. 1971.
Dynamic Models of Segregation.
Journal of Mathematical
Sociology 1:143-186.
Rule: each iteration, each
dot looks at its neighbours
and if less than 30% are
the same colour as itself, it
moves to a random empty
square
Conclusion:
Segregation can result from
wanting only a few
neighbours of a like colour

13. Simple, Conceptual Simulations
Such as Schelling’s
• Are highly suggestive
• Once you play with them, you start to “see” the
world in terms of you model – a strong version
of Kuhn’s theoretical spectacles
• They can help persuade beyond the limit of
their reliability
• They may well not be directly related to any
observations of social phenomena
• Are more a model of an idea than any
observed phenomena
• Can be used as a counter-example
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 13

14. Modelling a concept of something
Phenomena
conceptual model
Model
Exploration
with model
Analogical
Application
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 14

15. Abstract Theoretical Model
Simple model but
abstract – strong
inference within
model,
but weak
mappings to and
from the model
Object System
Model
Weak
Mapping
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 15

16. Complex Descriptive Model
Object System
Model
Complex but directly relevant model –
strong mapping to model,
weak inference within model
Weak Inference
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 16

17. Many different uses for an ABM
• To predict currently unknown data
• To explain observed data using complex
interaction mechanisms/agents/etc.
• To explore the theoretical consequences of
a set of complex mechanisms
• To illustrate an idea (show its possibility)
• As a way of thinking about stuff (analogy)
• To describe a small set of cases
• A way of mediating between stakeholders
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 17

18. Example 2: Culturally-Derived
In-Group Bias
Hales, D. & Edmonds, B. (2018)
Intragenerational Cultural Evolution and
Ethnocentrism, Journal of Conflict Resolution,
http://goo.gl/vS9uqN
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 18

19. Ethnocentrism or In-group Bias
• Ethnocentrism, and more generally in-group
bias, is a widely observed empirical
phenomena (in different aspects and in many
different ‘flavours’ (LeVine & Campbell 1972))
• People often divide the population into those
they consider as part of their group (their
‘type’), the in-group, and the rest who are
seen as outsiders, the out-group.
• Where such distinctions are made there is
often a propensity for more positive behaviour
towards the in-group, but why?
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 19

20. Tags and Groups
THE SNEETCHES
by Theodor Geisel (1961)
(aka. Dr. Seuss)
Now, the Star-Belly Sneetches
Had bellies with stars.
The Plain-Belly Sneetches
Had none upon thars.
Those stars weren't so big. They were really so small
You might think such a thing wouldn't matter at all.
But, because they had stars, all the Star-Belly Sneetches
Would brag, "We're the best kind of Sneetch on the beaches."
With their snoots in the air, they would sniff and they'd snort
“We'll have nothing to do with the Plain-Belly sort!"
And whenever they met some, when they were out walking,
They'd hike right on past them without even talking.
…
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 20

21. Previous Models
• There are a number of abstract models (Axelrod
and Hammond 2003; Hammond & Axelrod 2006;
Jansson 2013; Roitto 2015) where:
– agents are located on a spatial grid and evolve
– interaction and reproduction are localised on the grid
– agents can not change their behaviour or location
– the ethnic marker may change over generations
• In these, agents eventually come to favour their in-
group defined by an observable ethnic marker.
• These models focus on long-range, inter-generation
dynamics where no intra-generational learning can
occur.
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 21

22. The ethno-cultural tag model
• We explore within-generation cultural evolutionary
processes in non-spatial environments
• Agents do not reproduce or die but rather imitate
and innovate their beliefs and behaviours based
the results of interactions with other agents
• These other agents can be society wide rather
than localised, but are members of what they
consider to be their in-group or out-group
• Agents have a (fixed) ethnic marker and a
(changeable) cultural marker, so ethnicity-based
vs. culture-based cooperation can be explored

23. Agent Traits (in-group selector)
• Ethnic marker {1..NE}
• Cultural tag {1..NC}
• In-group selector {none, cultural,
ethnic, both}
• in-group strategy {donate, shirk}
• out-group strategy {donate, shirk}
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 23

24. in-group selector
Agents can only distinguish between other agents
by observing their ethnic marker and cultural tag
The in-group selector determines its in-group, as
one of:
– those with the same ethnic marker as itself
(ethnic);
– those with the same cultural tag as itself
(cultural);
– those with the same ethnic maker and cultural
tag (both);
– any other agent without restriction (none).
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 24

25. Agent strategies
Agents can hold one of four possible strategy
combinations in the donation game that is
played:
1) shirk against both the in-group and out-group
(ss);
2) donate to both the in-group and out-group
(dd);
3) donate to in-group, shirk on out-group (ds);
4) shirk on in-group, donate to out-group (sd).
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 25

26. Model Processes
Each tick all agents do the following as follows:
1.Partner Selection: with probability GB select
another in its in-group as self (if there is one)
otherwise another agent at random
2.Game Interaction: donate or not depending on
strategies and whether other is in- or out-group
3.Imitation: with probability LB select another in its in-
group as self (if exists) otherwise another at random, if
other’s payoff > its own, copy other’s selector, cultural
tag and strategies
4.Innovation: with small probabilities change (a)
cultural tag to a random other and (b) change one of
its strategies or selector
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 26

27. Demo of the simple model
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 27

28. Dominating Model Process
The following two processes seem to dominate
the dynamics:
•By chance, a new “seed group” of two mutual
cooperators appears, these have a high mutual
donation and hence are imitated by others; the
group grows quickly producing a surge of their
kind of agent
•After a while the group is “infected” by defecting
individuals who receive but do not donate (by
innovation), the payoff of agents in the group
gradually diminishes and eventually individuals
copy agents from a different group
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 28

29. Cultural Tag Group “Life Cycle”
Simulation Time 
DifferentCulturalMarkers

30. Conclusions about the model
• High donation rates occur between agents
sharing the same cultural tag
• Cultural tag groups trump ethnic groups
and no pure ethnocentrism emerges
• A form of ethnocentrism does emerge
based on in-groups defined by both the
cultural tag and ethnic marker combined
• Anything that could be interpreted as pure
ethnocentrism did not arise.
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 30

31. Interpretation Warning!
Real people in real societies do not change their beliefs and
behaviours based on simple imitation or random changes. People
are attached to particular beliefs and practices for many reasons
other than individual benefit. In fact they may be the basis of
identity itself and may be held even when they are of no benefit at
all. Social behaviours and beliefs result from a complex interplay of
upbringing, personal experience, social expectations and norms
and are not only the result of adaption of strategy and the basis of
judging who is “in-group”. Cultural groups may fall as well as rise.
Your social capital is at risk if you do not keep up your social
obligations. Membership of any cultural or ethnic group is subject
to terms and conditions. See website for details.
This model merely tests assumptions about the necessity for a
genetically-determined ethnic bias and explores how cultural
mechanisms might be responsible.
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 31

32. Example 3: A Complex Model of
Political Engagement
Fieldhouse, E & al. (2016) Cascade or echo chamber? A
complex agent-based simulation of voter turnout.
Party Politics. 22(2):241-256.
http://goo.gl/gnXjna
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 32

33. The Social Complexity of Immigration and Diversity was a 5-year project
with the Institute for Social Change and the Department of Theoretical
Physics at University of Manchester. It is funded under the “Complexity
Science for the Real World” initiative of the EPSRC to the tune of £2.7
million and lasted from July 2010 to Jan 2016.
The idea of the project is to apply the techniques and tools of complexity
science to real world issues, in this case of immigration and diversity. The
project will focus on: (1) why people bother to go out and vote and how
social influence within/across different communities affects this (2) how
people use social networks to find employment, e.g. how the impoverished
networks of immigrants may limit this and (3) inter-community trust.
Copy of Project Website:
http://cfpm.org/scid
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 33

34. Overall Structure of Model
Quant.Data
ExpertOpinion
Qual.Data
Plausible
Guesses!
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 34

35. Discuss-politics-with person-23 blue expert=false
neighbour-network year=10 month=3
Lots-family-discussions year=10 month=2
Etc.
Memory
Level-of-Political-Interest
Age
Ethnicity
Class
Activities
AHousehold
An Agent’s Memory of Events
Etc.
Changing personal
networks over which
social influence occurs
Changing personal
networks over which
social influence occurs
Composed of households of
individuals initialised from
detailed survey data
Composed of households of
individuals initialised from
detailed survey data
Each agent has a rich variety of
individual (heterogeneous)
characteristics
Each agent has a rich variety of
individual (heterogeneous)
characteristics
Including a (fallible) memory of
events and influences
Including a (fallible) memory of
events and influences

36. Different kinds of output for
calibration and validation
• Once you have a simulation you can
measure it to your heart’s content and
compare these to quant data
• And visualise these in many different ways
• You can observe developing social
structures
• You can zoom in to different levels, e.g.
observe what is happening to an individual
to check its plausibility
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 36

37. Example Output: why do people
vote (if they do)
Intervention: voter
mobilisation
Intervention: voter
mobilisation
Effect: on civic
duty norms
Effect: on civic
duty norms Effect: on habit-
based behaviour
Effect: on habit-
based behaviour
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 37

38. Simulated Social Network at 1950
Established
immigrants: Irish,
WWII Polish etc.
Established
immigrants: Irish,
WWII Polish etc.
Majority: longstanding
ethnicities
Majority: longstanding
ethnicities
Newer
immigrants
Newer
immigrants

39. Simulated Social Network at 2010
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 39

40. Psuedo-Narrative Output
Following a single, randomly chosen agent…
4: (person 578)(aged 5) started at (school 1)
17: (person 578)(aged 18) stops going to (school 1)
21: (person 578)(aged 22) moved from (patch 11 3) to
(patch 12 2) due to moving to an empty home
21: (person 578)(aged 22) partners with (person 326)
at (patch 12 2)
24: (person 578)(aged 25) started at (workplace 8)
24: (person 578)(aged 25) voted for the blue party
29: (person 578)(aged 30) voted for the blue party
Makes comparison to qualitative accounts easier
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 40

41. the SCID Modelling Approach
Complex Agent-Based Simulation ModelComplex Agent-Based Simulation Model
Micro Qual
Evidence
Micro Qual
Evidence
Macro Quant
Data
Macro Quant
Data
Abstract Simulation
Model 1
Abstract Simulation
Model 1
Abstract Simulation
Model 2
Abstract Simulation
Model 2
SNA ModelSNA Model Analytic ModelAnalytic Model
Social
Scientists
AB
Modellers
TheoreticalPhysicists

42. Concluding Summary
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 42

43. Conclusions
• ABM allows for a more straight-forward
representation of some complex systems
• In particular, heterogeneity, micro-macro
interaction, competing processes, dynamic
networks
• There are a range of goals and styles
• They can be deceptive in terms of credibility
and generality
• Difficult to completely validate – needs a
LOT of data, at many levels and kinds
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 43

44. To Learn More
• What is ABM? A similar talk + supporting materials,
Methods@Manchester, http://goo.gl/mazTAf
• Simulation for the Social Scientist, 2nd
Edition. Nigel
Gilbert and Klaus Troitzsch (2005) Open University
Press. http://cress.soc.surrey.ac.uk/s4ss/
• Journal of Artificial Societies and Social Simulation,
http://jasss.soc.surrey.ac.uk
• European Social Simulation Association,
http://essa.eu.org
• NetLogo, a relatively accessible system for doing
ABM with a big library of example models,
http://ccl.northwestern.edu/netlogo
An Introduction to Agent-Based Modelling, Bruce Edmonds, BIGSSS, Jacobs Bremen, July 2018, slide 44

45. The End
These slides will be put up at:
http://slideshare.net/BruceEdmonds
Bruce Edmonds: http://bruce.edmonds.name
Centre for Policy Modelling: http://cfpm.org
Paper about the Ethnocentrism Model (Open Access):
Hales, D. & Edmonds, B. (2018) Intragenerational Cultural Evolution and
Ethnocentrism, Journal of Conflict Resolution,
http://goo.gl/vS9uqN
Paper about the Voter Model (Open Access):
Fieldhouse, E & al. (2016) Cascade or echo chamber? A complex agent-based
simulation of voter turnout. Party Politics. 22(2):241-256.
http://goo.gl/gnXjna