A talk at the workshop on "Agent-Based Models in Philosophy: Prospects and Limitations", Rurh University, Bochum, Germany Abstract: ABMs (like other kinds of model) can be used in a purely abstract way, as a kind of thought experiment - a way of thinking about some aspect of the world that is too complicated to hold in our mind (in all its detail). In this way it both informs and complements discursive thought. However there is another set of uses for ABMs - empirical uses - where the mapping between the model and sets of observation-derived data are crucial. For these uses, one has to (a) use the mapping to get from some data to the model (b) use the model for some inference and (c) use the mapping again back to data. This includes both predictive and explanatory uses of ABMs. These are easily distinguishable from abstact uses becuase there is a fixed and well-defined relationship between the model and the data, this is not flexible on a case by case basis. In these cases the reliability comes from the composite (a)-(b)-(c) mapping, so that simplifying step (b) can be counterproductive if that means weakening steps (a) and (c) because it is the strength of the overall chain that is important. Taking the use of models in quantum mechanics as an example, one can see that sometimes the evolution of the formal models driven by empirical adequacy can be more important than the attendent abstract models used to get a feel for what is happening. Although using ABM's for empirical purposes is more challenging than for purely abstract purposes, they are being increasingly used for empirical explanation rather than thought experiments, and there is no reason to suppose that robust empirical adequacy is unachievable.

1. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 1
The Possible Evolution of Empirical ABMs
vs the danger of getting what you like
Bruce Edmonds
Centre for Policy Modelling
Manchester Metropolitan University

2. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 2
Models as Tools
• Models must be about something (or they are not
a model) but there are different ways they can
relate to whatever it is they are modelling, some
of which are very indirect
• Although we can often think of a model as a kind
of picture – the correspondence idea of modelling
– it is often more useful to think of them as a tool
• Example: the gas law equations that predict
temperature, pressure etc. of a gas
• Example: Schelling’s model of segregation which
is about an idea – a counterexample to an
assumption – not directly about anything
observed

3. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 3
Models as Specialised Tools
• “Model” is a very generic category, covering many
different kinds of construct (the “Model Muddle”)
• A lot of confusion results from lumping them in
together and making generic statements about
them as a collective (e.g. the theoretical virtues)
• From a philosophical perspective, an importance
difference is that they can have different purposes
• They can: predict, explain, illustrate, explore
consequences, communicate, be an analogy etc.
• Being good at one purpose does not necessarily
make a model good at another

4. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 4
Justifying Models
• Whilst one can be as sloppy as one wants,
playing with models in the privacy of one’s own
home, if one is presenting it in a public forum, one
should indicate how it is should be judged...
• ...in other words be crystal clear about its purpose
• So the audience can know how to assess its
goodness for its purpose, and hence how to take
on board the lessons learned
• Unfortunately, many authors are not clear, maybe
they are confused or simply want to impress by
implying uses which have not been demonstrated

5. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 5
Analogical Uses of Models
• Humans are good at using analogies – it is a
powerful way of thinking
• Indeed analogy may be at the root of how
language works (Lackoff 1987)
• Almost anything can be used as an analogy...
including models!
• A key property of analogies is that the relationship
from model to modelled is not precise, but flexibly
inferred by the audience each time
• In particular, the relationship with data is not
specified but left to the imagination

6. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 6
Empirical Uses of Models
• These are models where there is a precise and
direct relationship with some data
• This includes models whose purpose is
prediction, but also those with explanatory and
descriptive purposes
• In theory, the empirical fit to the data could be
checked by a machine
• Here, the model itself encodes knowledge (given
how it is set up etc.)…
• …although it may be that it also suggests further
human understanding or has other uses…

7. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 7
Intuitive understanding expressed in normal
language
Observations of the natural system of concern
Common-SenseComparison
“Common-Sense” Understanding

8. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 8
Intuitive understanding expressed in normal
language
Observations of the natural system of concern
Data obtained by measuring the
system
Models of the processes in the
system
EmpiricalComparisons
Using Empirical Models

9. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 9
Intuitive understanding expressed in normal
language
Observations of the natural system of concern
Models of the processes in the
system
Common-SenseComparison
Using models analogically
No precise
and direct
relationship

10. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 10
The Limitations of a Purely
Anthropomorphic Epistemology
• Just because what matters to us personally (as
humans) is our mental understanding, does not
mean that all knowledge comes down to this
• In particular, what is interesting to us, what is
simple, what is comprehensible to us etc. is not a
good guide to what is true or even as a guide to
what a good empirical model might be like
• This will become increasingly apparent as
machines (AIs) encode and act upon knowledge
that is so complicated that no human completely
understands it

11. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 11
The Advantage of Formal Models
• Not that they are particularly suited to representing
observed phenomena (e.g. social, economic,
biological…)
• But due to the fact that they can be unambiguously
transmitted – i.e. without re-interpretation by the
recipient
• This allows for a social way of working, where a
community of researchers can check, critique,
develop and use the formal models
• If any set of models undergoes extensive copying,
some variation and selection you get a form of
evolution (though like biological evolution this does
not necessarily imply a direction or progress)

12. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 12
E.G.: Models in Quantum Mechanics
• Mathematical (and derived computational) models
in quantum mechanics have been incredibly
successful empirically
• Although the models have developed, the
underlying mathematics (Schrödinger's wave
equation) has remained the same
• The analogical models used to get some human
understanding have changed according to long-
range fashions (Copenhagen, many-worlds etc.)
• The analogical models are important to help direct
research, but the empirically important core is the
empirical models

13. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 13
How do we want to select for good
models?
How we select for model (the way we determine
which models get preferentially copied in the future)
determines the natures of the outcomes of the
evolutionary process (given some assumptions):
• If we select models by their empirical success
then we might end up with complicated but
empirically good models
• If we select models by how interesting they are (to
us humans) then we might end up with relatively
simple and interesting set, but there is go reason
to suppose they are empirically good

14. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 14
The Limitations of Analogical Models
• Due to our unconscious ability of understanding
analogies, analogical models can give an
misleading impression of its potential generality
• The danger of analogical models are we take it:
1. too seriously, it is just a way of thinking about
stuff
2. as a good starting point for the development of
models for other purposes (e.g. empirical
explanation)
3. as somehow generally true merely
approximate
4. supported by seeking out confirmation

15. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 15
The Usefulness of Analogical Models
• As humans, we need some way of thinking about
unfamiliar or complicated stuff, analogies provide
way of doing this
• We do not need training in it, we are naturals
• For example, as a kind of meta-knowledge – how
to think about the horrible empirical models
• Thus they can form a part of a chain of models
each modelling/abstracting from the next, that
allow us to leverage useful tasks for systems
beyond our ability to understand directly
• Simple models can be an effective counter-
example, but only if the model is plausible!

16. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 16
Making models of models of …
Hegselmann-Kruse Model
epsilon-diagrams phase diagrams
Narrative Model

17. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 17
Making models of models of …
Data-Integration Simulation Model
Micro-Evidence Macro-Data
Reduced Simulation Models
Analytic Model
Even Simpler Simulation Model
Done by
social
scientists
Done by
physicists
Analogical Model

18. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 18
Will ABMs evolve empirically?
This is unclear it depends on a number of things:
• Whether there is enough copying of models
• Whether the variation that modeller introduce are
sufficient to cover enough of the possibilities
• How models are selected for success:
empirically? for interest? for simplicity?
How we do science matters! – A useful outcome is
not guaranteed by just doing what is interesting or
what we can (directly) understand

19. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 19
Summary
• Just as machines extend our physical abilities,
models extend our mental abilities
• But they are not all of a kind, they have different
purposes: theoretical exposition, empirical
explanation, prediction, description etc.
• Each purpose will entail different theoretical
virtues, e.g. simplicity for illustration, not
necessarily for empirical explanation etc.
• The virtues are not just a matter of personal
choice
• Care needs to be taken not to conflate models
established for different purposes

20. The Possible Evolution of Empirical ABMs, Bruce Edmonds, ABMs in Philosophy, Bochum, March. 2019. slide 20
The End
Bruce Edmonds
http://bruce.edmonds.name
Centre for Policy Modelling
http://cfpm.org
A version of these slides are available at:
http://slideshare.net/BruceEdmonds
@