How social simulation could help social science deal with context

How social simulation could help social science deal with context, Bruce Edmonds, Social Simulation, Stockholm, August 2018, 1
How social simulation could help
social science deal with context
Bruce Edmonds
Centre for Policy Modelling
Manchester Metropolitan University

…but first an Advertisement!

Talk Outline
1. Some personal motivation
2. Talking about “Context”
3. How Social Science effectively avoids
dealing with context
4. Approaching context from narrative accounts
5. Implementing context-sensitive behaviour in
social simulation
6. Concluding Discussion

Some personal motivation
Part 1:

The Complexity of Vision
• Although easy to do, vision is very complex
• Done using processes that we are not aware of
• E.g. we are not (usually) aware of shifting focus

The Complexity of Thought
• Although easy to do, thought is
very complex
• Done using some processes
that we are not aware of
• E.g. we are not (usually)
aware of shifting context

Talking about “Context”
Part 2:

The Difficulty of Talking about
Context
• The word “context” is used in many different
senses across different fields
• Somewhat of a “dustbin” concept resorted to
when more immediate explanations fail (like
the other “c-words”: complexity & creativity)
• Problematic to talk about, as it is not clear that
“contexts” are usually identifiably distinct
• Mentioning “context” is often a signal for a
more “humanities oriented” or
“participatory/involved” approach and hence
resisted by “scientists” who are seeking
general laws

A (simplistic) illustration of context from the
point of view of an actor

Situational Context
• The situation in which an event takes place
• This is indefinitely extensive, it could include
anything relevant or coincident
• The time and place specify it, but relevant
details might not be retrievable from this
• It is almost universal to abstract to what is
relevant about these to a recognised type
when communicating about this
• Thus the question “What was the context?”
often effectively means “What about the
situation do I need to know to understand?

Cognitive Context (CC)
• Many aspects of human cognition are context-
dependent, including: memory, visual perception,
choice making, reasoning, emotion, and language
• The brain somehow deals with situational context
effectively, abstracting kinds of situations so
relevant information can be easily and
preferentially accessed
• The relevant correlate of the situational context
will be called the cognitive context
• It is not known how the brain does this, and
probably does this in a rich and complex way that
might prevent easy labeling/reification of contexts

Social Context
• Since humans are fundamentally social beings…
• …social context is often most important
• e.g. an interview, a party or a lecture
• But social context may be co-determined, since:
– Special rules, norms, habits, terms, dress will be
developed for particular social contexts
– The presence of special features, rules etc. make the
social context recognisable distinct
• Over time social contexts plus their features
become entrenched and passed down
• Social Context arises and is so recognisable as a
result of cognitive and external features (e.g.
building a lecture hall)

How Social Science effectively avoids
dealing with context
Part 3:

Why context is unavoidable
• Many aspects of human cognition are known to
be highly context-sensitive, including: memory,
preferences, language, visual perception,
reasoning and emotion
• There is much qualitative research that has
documented instances where a specific context
is essential to understanding observed behaviour
• Simple observation and introspection tells us that
behaviour in different kinds of situation is not
only different but decided on in different ways
(e.g. in a lecture and a football game)

However despite this, in quantitative
social science….
• Almost all formal models of human behaviour
(mathematical, logical or computational) are
generic – they do not exhibit this sharp context-
dependency
• Another stream of models (models fitted to or
tested against data) consider a single model (at a
time) against a set of data that derives from many
different contexts – only interested in what
behaviour is “context independent”
• This seems to me to be a case of massive
“wishful thinking”

Context-Dependency and
Randomness
Lots of
information
lost if
randomness
used to
“model”
contextual
variation

Qualitative research…
• Does take context seriously, but has (largely) often
limits iteself to description within specific contexts
• Knowledge is only useful if it is to some extent
applicable in a new situation (even if only slightly new)
• Analogical reasoning can project knowledge from one
context upon another, and this can give insights
(interesting hypotheses) but not reliable knowledge
• This kind of research often avoids responsibility for
the application of knowledge gained from its studies
(necessarily in a different situation to where it was
observed) whilst implying it is somehow useful

Context in the Social Sciences
– the elephant in the room
To summarise:
• We have one set of researchers who are ignoring context,
optimistically hoping to find general patterns even though
they must know context must be crucial in many cases
• Another set of researchers refuse to look at what is
general across contexts or how contexts might
systematically affect behaviour
• Few are seriously trying to study social context itself – how
it works, what regularities there are, how to identify it, how
to model its impact, when we can generalise across a set
of contexts
Social context is central to human behaviour but
effectively not researched much

Some ways forward
• Keeping the data and simply NOT summarising it (at
least not prematurely)
• Data mining local patterns to detect commonality of
multiple models/measurements across similar contexts
• More complex simulation models with context-dependent
cognitive models
• Context-oriented microsimulation models
• Context-sensitive visualisation techniques
• Integrating personal/anecdotal accounts of behaviour –
making use of qualitative evidence with its context
• Not leaving the context(s) – understanding and acting
within the sphere of a shared context
• Staging abstraction more gradually
• Clusters of related models covering different contexts
1
2
3

Approaching context from qualitative
narratives
Part 4:

Integrating Aspects of Qualitative
Evidence into ABMs
• Identifying kinds of context (those over which we
might expect some regularity in terms of shared
norms, expectations etc.) might allow suggestions
from qualitative evidence to be incorporated into
agent-based models
• For example by providing the repertoire of possible
strategies in the context which are decided between
• This could greatly enrich agent-based models
allowing in some of the social “mess” we observe
• However this requires new methods to analyse
narrative evidence in a context-depenent manner

Identifying the ‘right’ contexts
• It is hard since people assume context, it is
usually left implicit, indeed people are often not
aware of the context they are assuming
• However…
– Socially entrenched contexts can be identified
– When giving examples (could you imagine doing that in
situation X) people are relatively good at recognising
when the context is wrong
– Our intuitions are a good starting point, as long as we
are aware they might be wrong
• No well-developed methods – this needs further
research

Different Aspects Illustrated
Universe of Knowledge
Knowledge indicated by current cognitive context
Knowledge that is possible to
apply given circumstances
Cause1 & Cause2… 
Result1 & Result2…
Event1, event2, etc.

CSNE Analysis Framework
1. Context: the kind of situation one is in that
determines the ‘bundle’ of knowledge that is
relevant to that kind of situation
2. Scope: what is and is not possible given the
current situation and observations
3. Narrative Elements: the narrative elements that
are mentioned assuming the context and scope

About Scope
• By “scope” I mean the reasoning as to which
knowledge is possible given the circumstances
• For example, if all the seats are taken in a lecture,
then some of the norms, habits and patterns as to
where one sits might not apply
• Reasoning about scope can be complex and is
done consciously
• However once judgments about scope are made
then they tend to be assumed (i.e. are fixed),
unless the situation changes critically

Scope vs. Cognitive Context
• Both scope and cognitive context determine which
knowledge is useful for any particular situation
that is encountered
• However, they play different roles:
– CC is learnt using pattern recognition over a long time,
but then is largely a ‘given’, is almost impossible to
change when learnt, is quick and automatic and is
socially rooted
– Scope is largely reasoned afresh each time, taking
effort to do so, is possible to re-evaluate but only if
needed, and is more individually oriented

Narrative Elements
A variety of narrative structure elements are
possible, including:
– Causal stories: A … resulted in … B
– Sequences: A … then … B … then C
– Choices: had to choose between … A and B
– End points: which resulted in A which was a
disaster/really good/…
– Parallelism: A … happens at the same time as ….B
Some possible structures for these suggested by:
(Abell 1992) or (Toulmin 2003)

Narrative
Text
Identifying
Contexts
Identifying
Scope
Identifying
Narrative
Elements
Micro-Level
Specification for
Agent
Behaviour
Agent Program
Code
Using an CSNE analysis in ABM

Some Example Analyses
using narrative examples from:
Bhawani, S. (2004) Adaptive Knowledge Dynamics and Emergent
Artificial Societies: Ethnographically Based Multi-Agent Simulations
of Behavioural Adaptation in Agro-Climatic Systems. Doctoral
Thesis, University of Kent, Canterbury, UK.
(thesis linked from ‘Relevant Papers’ at http://cfpm.org/qual2rule)

Hypotheses about relevant contexts
for the interviewed stakeholder
Different perspectives from which the narratives
seem to be told:
• “survival” – things are continually getting worse
and the primary goal is to keep in farming, battle
against nature etc. to avoid bankrupcy
• “comfort” – conditions are comfortable with no
immediate survival threat, one could stop worrying
so much and take things a little easy
• “entrepreneur” – one is looking for big profit,
taking risks if necessary

Survival ComfortStart Entrepreneur
Conditions Stable
and ensuring no
foreseeable threat
An opportunity
arises to make
more money
Opportunity
disappears
Existential threat
becomes
feasible
An illustration of the relevant cognitive
contexts

Quote 1 (p. 113) and CSNE Analysis
“The one conundrum here is that there are more people in
the East who want to … upgrade to more wheat allied
products, that may alter the value of the end product to us.
You see the worst thing that has happened to us worldwide
is the collapse of the Eastern economy... but it is coming
back again now and that actually may help us again. It is a
great shame because we were getting into the Eastern
markets and it was beginning to grow and suddenly it
collapsed.”

Quote 2 (p. 127) and CSNE Analysis
“…we have often had this conversation around this table.
Some people don't want to maximize profit.... They are
happier to take a slightly easier, lower level approach and
have an easier life, and not make quite so much money....
And I can relate to that... But because I'm a tenant I don't
own my own land... Everything we farm is rented and
therefore we have an immediate cost, the first cost we meet
is to our landlord and that tends to go up.”

Narrative
Text
Identifying
Contexts
Identifying
Scope
Identifying
Narrative
Elements
Agent context
structure
What agent
reasoning
about scope
occurs
Specification
of sequences,
plans,
branches
Agent context
recognition
and retrieval
rules
Reasoning
rules about
scope
Specific code
for narrative
elements
Micro-level
specification
Agent
architecture
structuring
program code

Implementing Context-Sensitive
Agents in Social Simulations
Part 5:

Ignoring Context
• Some social simulation simple ignores that their
agents are making decisions in different contexts
and hopes that does not change outcomes much
• Other modelling is conceived to represent within a
single context, in which case it can be ignored but
only if
– everyone is using the same idea of this context
– there is no significant “leakage” of causation from
outside the background, that is the scope is wide
enough to include all significant influencing factors
– The actors/organisms don’t deal with the same situation
as different cognitive contexts

Some Simulation Work addressing
Context-Dependency in Cognition
• (Schlosser & al 2005) argue that reputation is context
dependent
• (Edmonds & Norling 2007) looks at difference that
context-dependent learning and reasoning in an
artificial stock market
• (Andrighetto & al 2008) show context-dependent
learning of norms is different form a generic method
• (Tykhonov & al 2008) argue that trust is context
dependent
• (Fieldhouse & al 2016) have different social networks
and behaviours for some different contexts

Comparison in an Artificial Stock
Market
Environment:
• Traders (n context, n straight GP)
• 1 Market maker: prices and deals: 5 stocks
• Traders buy and sell shares at current market
price, but do not have to do so
• Traders have memories, can observe actions of
others, index, etc.
• Modelling ‘arms-race’
• Actions change environment

Basic Cognitive Model
• Rich, automatic, imprecise, messy cognitive
context recognition using many inputs (including
maybe internal ones)
• Crisp, costly, conscious, explicit cognitive
processes using material indicated by cognitive
context
Context
Recognition
Context-Structured
Memory
Reasoning/plan
ning/belief
revision/etc.

Example – models in the cognition of a
trading agent
700
750
800
850
900
950
750 850 950
Volume - past 5 periods
Volatility-past5periods

The model contents in snapshot of
one trader
model-256 priceLastWeek [stock-4]
model-274 priceLastWeek [stock-5]
model-271 doneByLast [normTrader-5] [stock-4]
model-273 IDidLastTime [stock-2]
model-276 IDidLastTime [stock-5]
model-399
minus
[divide
[priceLastWeek [stock-2]]
[priceLastWeek [stock-5]]]
[times
[priceLastWeek [stock-4]]
[priceNow [stock-5]]]

0
5000
10000
15000
20000
25000
30000
0 100 200 300 400 500
Time
TotalValueofAssetsTotal Assets in a Typical Run
Black=context, White= non-context

Implications for Simulation Modelling
• Simulations which represent agents, that in the
real world would be acting with respect to different
contexts but who are represented with an
essentially uniform behaviour need to justify this
• Social simulation might be missing a class of
phenomena that is essentially context-dependent
– How social contexts emerge
– Cross-cultural interaction where different contexts
assumed
• Context-dependent cognitive models in
simulations are feasible but are more work

Concluding Discussion
Part 6:

What is Essential to (empirical)
Science?
• Validity: agreement (in some way) of models to what we
observe, not science otherwise
• Formality: formal models (maths, simulation, etc.) are
precise and replicable – essential to being able to build
knowledge within a community of researchers
• Simplicity: ability to analyse/understand our models,
nice to have but unattainable in general
• Generality: the extent of the applicability of a single
model (i.e. its scope), there needs to be some small
generality to apply models in places other than where
developed, but wide generality not necessary
This talk has suggested the following trade-off:
reducing the generality of each behaviour,
and tolerating complexity
to achieve more validity in the face of complexity

Context-Dependency
and “Being Scientific”
• If the relevant context can be reliably identified
then context-dependency is not the same as
subjectivity (even if there are a some hard cases
that escape definition)
• Generality is nice if you can get it, but its no good
pretending to have it if it is inaccessible
• Science should adapt to what it wishes to
understand, not the other way around
• Useful, validated models of context-dependent
phenomena are more scientific since they reflect
more of what is actually happening, not less

Don’t Prematurely Summarise!
• Traditionally Science has summarised its data
and conclusions using averages, linear regression
models, aggregate graphs, etc. etc.
• …and thus has missed some of the complexity,
the fundamental variety and context-dependency
of social phenomena
• We no longer have to do this!
• Agent-based modelling (along with other
advances, such as the ability to store lots of
original data etc.) means we can preserve, model
and explore this richness

Conclusions
• Social science has largely ignored or by-passed
social context
• …not becuase it is not important – it is central to
many social phenomena
• ...but becuase it is hard to deal with using
simplistic models
• ...and because context-dependency has been
associated with subjectivity and not scientific
• Social simulation has the tools to address
these problems, and could thus allow it to take
a central role in the social sciences

These slides will be at: http://slideshare.net/BruceEdmonds
Bruce Edmonds: http://bruce.edmonds.name
Centre for Policy Modelling: http://cfpm.org
Collected papers and slides of mine on context at:
http://bruce.edmonds.name/context
The End!

How social simulation could help social science deal with context

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