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Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 1
Context in Environmental Modelling– the room around the elephant
Bruce EdmondsCentre for Policy Modelling,
Manchester Metropolitan University
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 2
Acknowledgements
Many thanks to all those with whom I have discussed these ideas, including: Emma Norling, Nick Shryane, Jason Dykes, Scott Moss, those at
the Conference Series on “Modelling & Using Context”, the regulars at the Manchester Complexity
Seminar and those in the SCID Project.
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 3
Some Questions about Context
• How important is the context when modelling process/aspect/system X/Y/Z?
• How much can we ignore context…• …or, conversely, how much of the context
do we have to include within our models?• If we include context-dependency does that
stop us being scientific?• How can we square the context-dependency
of the observed/involved world with our models of that world?
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 4
Talk Outline
1. Context-dependency in the environment
2. Context-dependency in human behaviour
3. Some defensive responses to context-dependency
4. Some possible ways forward
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 5
Note on 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-word”, complexity)
• 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
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 6
Ecological Context-DependencyPart 1:
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 7
Ecological Context
• A certain kind of environment might provide certain affordances/difficulties
• Organisms adapt to exploit these but also create new affordances/difficulties
• Migration between similar ecologies makes organisms ready to exploit each type available
• The organisms are only fully understandable in their ecological context – the web of other organisms and their environment
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 8
A (colourful!) Picture of the World
• Each square (patch) is a different, well-mixed location
• There are 15 kinds of location with individuals in each (4 bit string)
• Small stars are herbivores, circles those who have eaten another (the bigger the more it has eaten)
• Different colours indicate different species (not all species are visually distinguishable)
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 9
Brief (!) Model Outline
• Basic energy economy (life tax, 90% transference, reproduction at 3, birth at 1 etc.)
• Patches and organisms have a binary vector (lengths 4 and 100 respectively)
• Fixed 100x100 random matrix made at start that broadly determines…
• …who can eat who (or who extract energy from environment) determined by eater & eaten’s binary strings (sum of entries in matrix at rows and columns indicated by 1s)
• Slow processes of mutation, migration etc.
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 10
Simulation at (up to) Reference Point
CarnivoresAppear
First SuccessfulHerbivore
Simulation“Frozen”
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 11
From this point on…
50 times for each of 16 different “aspects” (as well as none, the base case)…• Reset world to this point• “Block” interaction on one of the dimensions (the
entries in the matrix indicated by 1s in that column/row number are not summed)
• Simulate the world for a further 100 ticks (with different random seed each time)
• Measure the genetic diversity of the population overall and by each niche type (average hamming distance between all distinct agents)
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 12
Affect of Blocking Different Aspects of Interaction (av. over 20 runs after 100 ticks, ±2SD)
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 13
Effect of Blocking Aspects of Interaction by Aspect
Base Case(no blocking)
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 14
Implications of Environmental Context-Dependency
• Whilst there are some underlying universals that affect the environment (water, genetics, energy…)
• What characterises “the” environment is that it is not singular but a complex, overlapping patchwork of different ecological contexts
• We can gain some understanding of what is happening within each context, but generic understandings across these can be weak
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 15
Context-Dependency in Human Behaviour
Part 2:
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 16
A (simplistic) illustration of context from the point of view of an actor
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 17
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?
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 18
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
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 19
The Context Heuristic
• The kind of situation is recognised in a rich, fuzzy, complex and unconscious manner
• Knowledge, habits, norms etc. are learnt for that kind of situation and are retrieved for it
• Reasoning, learning, interaction happens with respect to the recognised kind of situation
• Context allows for the world to be dealt with by type of situation, and hence makes reasoning/learning etc. feasible
• It is a fallible heuristic…• …so why do we have this kind of cognition?
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 20
Social Intelligence Hypothesis
• Kummer, H., Daston, L., Gigerenzer, G. and Silk, J. (1997)
• The crucial evolutionary advantages that human intelligence gives are due to the social abilities it allows
• Explains specific abilities such as imitation, language, social norm instinct, lying, alliances, gossip, politics etc.
• Social intelligence is not a result of general intelligence, but at the core of human intelligence, “general” intelligence is a side-effect of social intelligence
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 21
An Evolutionary Perspective
Social intelligence implies that:• Groups of humans can develop their own
(sub)cultures of technologies, etc. (Boyd and Richerson 1985)
• These allow the group with their culture to inhabit a variety of ecological niches (e.g. the Kalahari, Polynesia) (Reader 1980)
• Thus humans, as a species, are able to survive catastrophes that effect different niches in different ways (specialisation)
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 22
Implications of SIH
• That different complex “cultures” of knowledge are significant
• An important part of those cultures is how to socially organise, behave, coordinate etc.
• One should expect different sets of social knowledge for different groups of people
• That these might not only be different in terms of content but imply different ways of coordinating, negotiating, cooperating etc.
• That these will relate as a complete “package” to a significant extent
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 23
Social Embedding
• Granovetter (1985) • Contrasts with the under- and over-socialised
models of behaviour• That the particular patterns of social
interactions between individuals matter• In other words, only looking at individual
behaviour or aggregate behaviour misses crucial aspects
• That the causes of behaviour might be spread throughout a society – “causal spread”
• Shown clearly in some simulation models
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 24
Illustration of Causal Complexity
Lines indicate causal link in behaviour, each box an agent (Edmonds 1999)
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 25
Implications of Social Embedding
• In many circumstances agents can learn to exploit the computation and knowledge in their society, rather than do it themselves (invest in what Warren Buffet invests in)
• Knowledge is often not explicit but is something learned – this takes time
• This is particularly true of social knowledge – studying guides as to living in a culture are not the same as living there for a time
• Social embedding means that human behaviour can not be understood well separate from its cultural context
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 26
The Social Co-Development of Shared Recognised Context
• Over time, due to their similarities, certain kinds of situation become recognised as similar by participants
• This facilitates the development of a set of shared habits, norms, knowledge, language etc. that is specific to the context
• The more this happens the more distinctive that kind of situation becomes and hence more recognisable by newcomers
• Eventually these may become institutionalised in terms of infranstructure, training etc. (e.g. how to behave in a lecture theatre)
• This co-development of context may be the reason for its social/evolutionary value
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 27
Implications of the Context-Dependency of Human Behaviour
• Behaviour of observed actors might change sharply across different social contexts
• The relevant behaviour, norms, kinds of interaction etc. might also change
• Social contexts are co-developed and changing• They may be different for different groups• Some kinds of social behaviour seem to be inherently
context-dependent (compliance)• It is unlikely that a lot of key social knowledge, norms,
behaviour etc. will be generic• Models that assume a cross-context engine of human
behaviour may be deeply misleading!
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 28
My Central Point
• Given the sharp context-dependency of both human behaviour and the environment…
• …how is it that a lot of our models use generic models of human behaviour and/or the environmental response?
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 29
Defensive ResponsesPart 3:
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 30
Some Possible Responses
• Its too difficult, I’ll ignore it• I am looking at the wider/more general picture, what is
common across contexts• I treat intra-context variation as random noise• I have included context, it is the variables a, b, c etc.
which vary with the context• I am acting within context only• I am only modelling a single context• It is not scientific • I need an analytic expression for my model• Use natural language/analogical models only• I don’t have enough data
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 31
Ignoring Context
• Much modelling happens with a single context in mind, 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
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 32
The “Simple is more General” Fallacy
• If one has a general model one can make it more specific (less general) by adding more processes/aspects…
• …in which case it can become more complex• However, the reverse is no true…• If one simplifies/abstracts then you don’t get a more
general model (well almost never)!– there may be no simpler model that is good enough for
your purpose– But, even if there is, you don’t know which aspects can
be safely omitted – if you remove an essential aspect if will be wrong everywhere (no generality)
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 33
Context-Dependency and Randomness
Lots of information lost if randomness used to “model” contextual variation
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 34
Scaling by Size
• Look at variance as system size increases…• Does variance as a proportion of size disappear?• In this case Law of large numbers does not apply• Simple examples:
• Kaneko (1990): parallel globally coupled chaotic processes• Edmonds (199?): scaling Brian Arthur’s “El Farol Bar” Model
Size
Variance(scaled by size)
Contextual variation
Model with random noise
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 35
Context-Dependencyand “Being Scientific”
• If the relevant context can be reliably indentified 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 you can’t
• Science should adapt to what it wishes to understand, not the other way around
• It does mean (often) an acceptance that general/generic approaches are not useful
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 36
Analogical Thinking
• Humans are good at using analogies, relating an idea or example from one context to another in a rich, relevant and flexible manner – it is a powerful method of thought
• They build the mapping from the analogy to the a context “on the fly”, largely unconsciously
• The mappings are different each time an analogy is applied, thus not a reliable source of transmittable knowledge – each person might build a different mapping unless they inhabit the same context
• Many published models do not have an explicit mapping to a domain, but are used more as analogy
• This is sometimes hidden, so when a simulation (or analytic model) does not directly map to observations but to an idea which then applies as an analogy to the domain and not directly, this gives a spurious impression of generality
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 37
Some Ways ForwardPart 4:
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 38
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-sensitive microsimulation models• Context-oriented visualisation techniques• Use of “mundane”, context-specific models of human behavior rather
than ambitious generic ones• Integrating personal/anecdotal accounts of behaviour – making use of
qualitative evidence• Not leaving the context(s) – acting within the normal sphere of shared
and relevant situations• Staging abstraction more gradually• Clusters of related models
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 39
Cleveland Heart Disease Data Set – the processed sub-set used
In processed sub-set:• 281 entries• 14 numeric or numerically coded attributes• Attribute 14 is the outcome (0, 1, 2, 3, 4)• Some attributes: age, sex, resting blood
pressure (trestpbs), cholesterol (chol), fasting blood sugar (fbs), maximum heart rate (thalach), number of major vessels (0-3) colored by flourosopy (ca)
• From the Machine Learning Repository
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 40
Fitting a Global Model (R=56%)
Num = -0.01*age + 0.17*sex + 0.20*cp + 0.00*trestbps + 0.10*restecg + -0.01*thalach + 0.23*exang + 0.18*oldpeak + 0.16*slope + 0.43*ca + 0.14*thal + -0.60 (+/- 0.83)
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 41
Looking for Clusters in HD Data Set (Start of Process)
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 42
Final Set of Clustered Solutions
• Final solution set after some time.
• Still complex but some structure is revealed
• Note presence of “fbs” despite not being globally correlated and that “chol” helped define the context space
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 43
A useful context is one that:– includes related models with different
goals/predictions but similar scope
Clusters of Model Scopes suggest a Context
M1 M2
M1
suggests a context
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 44
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/planning/belief
revision/etc.
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 45
Example – models in the cognition of a trading agent
700
750
800
850
900
950
750 850 950
Volume - past 5 periods
Vol
atili
ty -
pas
t 5
perio
ds
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 46
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]]]
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 47
0
5000
10000
15000
20000
25000
30000
0 100 200 300 400 500Time
To
tal V
alu
e o
f Ass
ets
Total Assets in a Typical Run
Black=context, White= non-context
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 48
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 makes 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
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 49
Conclusions
• Ignoring it and simply hoping it won’t matter is not an option (if we are serious about our project)
• There are ways forward to meaningfully make progress in dealing with context-dependency
• And some of these involve the integration of qualitative/in situ approaches with quantitative/formal modelling
• We will need a LOT more data both multi-dimensional and at a finer-granularity, but this is starting to come on stream
• Context seems to be an important factor impeding the integration of both: action-oriented and model-based approaches, as well as quantitative and qualitative approaches
• Please help
Context in Environmental Modelling - the room around the elephant, Bruce Edmonds, iEMSs, Leipzig, July 2012, slide 50
The End
Bruce Edmondshttp://bruce.edmonds.name
Centre for Policy Modelling http://cfpm.org
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