Agent-based modelling
A question of scale
Mark Lake
Institute of Archaeology
Agenda
What is agent-based modelling (ABM)?
Scale and ABM
Reasons for archaeological interest in ABM
Data requirements of ABM
Example of ‘ethnographic’ scale agent-based GIS
Concluding obser vation
Points for discussion
Agent-based modelling
An agent-based computer
simulation implements a
collection of (often
interacting) artificial
agents carrying
out one or more tasks in
an artificial environment
Paradigmatic example is
Epstein and Axtel’s 1996
Sugarscape
Scale and ABM
ABM is good for exploring how micro-scale
processes give rise to macro-scale phenomema
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Archaeological interest
in ABM
Growing archaeological interest driven by
scalar issues
‘New science’ of complexity (especially emergence) seen as
overcoming flaws in 1970s systems thinking
Methodological individualism of much contemporary
evolutionary and Dar wian archaeology
Widespread interest in problem of agency, epecially when agency
is construed as a property of the relationship bet ween
individuals and scociety
Post-processual preference for ‘ethnographic’ scale of analysis
which deals with problems of experience and meaning
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Scale of archaeolological
ABM
Individuals
Mithen 1990, Doran et al. 1994, Lake 1995, Bousquet 2001,
Costopoulos 2001, Lake 2001, Wilkinson et al. 2007, Scholnick &
Premo in prep., Sept. et al. in prep., Burke in prep.
Household / small group
Dean et al. 2000, Kohler et al. 2000, Lake 2000, Lake et al.
2005, Barton et al. n.d., Wilkinson et al. 2007.
Larger unit
?
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Data and ABM
Input
Output
Continuous
Scale appropriate
to agent
Any scale
Discontinuous
Scale appropriate
to agent
Any scale
Scale appropriate
to agent
Any scale
Spatial
Aspatial
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An ‘ethnographic’ ABM
Cognitive maps
(GIS)
Environment
(GIS)
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Agents
Representation
of world
Capable of reproduction
Social
Cognitive maps
(GIS)
Reactive
Autonomous
Environment
(GIS)
Situated
Goal-directed
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Palaeoenvironment
Model of the
abundance of hazel
Continuous surface
Raster map
(interpolatation from point
data or theory driven?)
Ethnographic scale
30km * 40km at
50m x 50m resolution
= 480,000 cells
Hazel
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Input data and principles
Pollen maps (Isochrone)
Provide: coarse-grained information about regional presence or
absence of species. In this case oak, hazel, birch, ash at 7000BP
Environmental factors (soil, climate, etc.)
Provide: information about potential of land to support a given
species and therefore potential single species abundance
Ecological principles (competition)
Provide: information about extent to which potential species
abundance will be realised
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Environmental factors
Land capability for
woodland
Basic features of the postglacial
climate established by 7000BP
Climate is a good ‘first sieve’
Exposure is a proxy for windthrow,
droughtiness and wetness
Final model combines climate and
exposure (omits nutrients)
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Quantitative model
Single species
abundance
Mathematical
model
Intolerant
Tolerant
species
b = 70
100
a=9
14
k=4
14
1.
2
8
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Quantitative model
Single species
abundance
GIS model
Implement mathematical models
using map algebra
85% landcover
0 % landcover
Hazel
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Quantitative model
Adjusted species
abundance
Mathematical
model
Succession =
birch
hazel
oak
alder (in wet)
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Quantitative model
Adjusted species
abundance
GIS model
Create single species models for
birch, hazel, oak, ash
Combine using map algebra to
model the effect of competition
85% landcover
0 % landcover
Hazel
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Validation
Relative species abundance
Predicted by applying model to average
land capability within 5000m of
pollen cores
Loch Gorm
Sorn Valley
Loch a’ Bhogaidh
Land
capability
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Sample output
Agents starting
at Bolsay Farm
Risk-averse foragers remain
on the Rhinns of Islay
Risk-taking foragers explore
the Rhinns, but ultimately
move to south of island
All
artefacts
Scrapers
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Concluding obser vation
Many (most ?) archaeological ABMs require
Relatively large scale (fine-grained) ...
... Spatially continuous input
Much (most ?) of the available data is
Relatively small-scale (coarse grained) and ...
... discontinuous
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Points for discussion
How good are we at
Combining datasets of different scales?
Interpolating small-scale data to produce large-scale models?
Interpolating point data to produce continuous models?
Disseminating input models to facilitate wider community
validation of ABM?
Providing adequate metadata for input models?
Acknowledgements
Mark Lake’s research integrating GIS and ABM
has been funded by:
Leverhulme Trust award F/07134/2
Arts and Humanities Research Council award APN111956
Leverhulme Trust Special Research Fellowship
NERC award GR3/9540 (to Prof. Steven Mithen)
Example
Archaeological problem
The Southern Hebrides
Mesolithic Project
(directed by Steven Mithen)
had obtained clear evidence
that Mesolithic people on
Islay and Colonsay har vested
large numbers of hazelnuts
Mithen ed. 2000
Was the distribution of hazelnuts the primary
determinant of land-use by relatively mobile foragers
who sporadically visited the islands?