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Personal Understanding and Publically Useful
         Knowledge in Social Simulation




                                            Bruce Edmonds
                               Centre for Policy Modelling,
                           Manchester Metropolitan University


Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 1
Some “stylized facts” about PhD
Students (and other new researchers)
• They are very keen to tell people all the
  details of what they have done
• They often come across some text/person
  which transforms their way of thinking
• They often want to convince the world of
  their new conceptual framework or
  methodology
• Their language can be very bound up with
  their “home” research group, sometimes to
  the extent that others find it hard to
  understand them
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 2
This Talk will…

• …attempt to explain why these occur
• Point out some mistakes and confusions that
  some researchers make
• To make a distinction between personal and
  “public” knowledge
• Appreciate the value of non-communicable
  knowledge
• To encourage you to think about what you
  communicate to other researchers and how
• …and thus help you to have a greater impact
  in terms of reporting your research

   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 3
Outline of Talk



   1. Introduction: Motivation and Some
      Preparatory Philosophy
   2. Personal Knowledge
   3. Public Knowledge
   4. Some Complications
   5. Sharing Different Kinds of Things
   6. Some Examples

   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 4
Part 1:

      Motivation and Some Preparatory
                 Philosophy


Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 5
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

    Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 6
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)
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 7
SIH In academic life

• Different communities of practice develop
  within different academic groups
• There will be a core of (often implict)
  practices, styles, techniques, assumptions
  that define that group and hence are (pretty
  much) not alterable
• Other items (often explict) will be the focus
  of debate within the community such as
  models, data sets, explicit hypotheses etc.
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 8
Kuhn and scientific revolutions

• Kuhn (1962)
• Observed that science often progresses in
  terms of fairly sudden revolutions rather
  than via a gradual build up of knowledge
• “Revolutionary science” involves a change
  in paradigm
• In between revolutions: “normal science”
• Effect of “theoretical spectacles” where data
  is selected dependent on paradigm
• Different paradigms are incommensurable
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 9
Example: Continental Drift

• From Kuhn (1962)
• That the earth’s crust was composed of huge
  “floating” plates that slowly moved was
  resisted by established researchers for a long
  time until the weight of evidence became
  overwhelming and a sufficient of (mostly
  younger) researchers had adopted this (Kuhn’s
  “revolutionary science”)
• In contrast, ideas/results that are compatible
  with existing ideas can be incrementally added
  with relative ease (“normal science”)
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 10
Explanatory Coherence




• Thagard (1989)
• People choose whether to believe something
  depending on how it would affect the
  coherency of the (augmented) network of
  (relevant) beliefs
  Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 11
Growing an internal “Ecology” of
Ideas
• As the network of ideas, associations and
  knowledge grows and is pruned a stable
  structure appears
• This is (usually) resistant to ideas that are
  incoherent with what is already there
• Asking others to change whole parts of the
  structure is unlikely to be accepted easily
• Ideas that strengthen the existing structure
  (giving it more coherence) are more likely
  to be accepted but only if it delivers a lot
  Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 12
Theoretical Spectacles

• Kuhn (1962): when we have adopted a theory
  we tend to filter what we see:
  – We notice aspects of data/observations that agree
    with it or are explained by it
  – We don’t notice (or explain away) anything that
    does not fit with the theory
• We see the world “through” the present theory
• This effect is even stronger with agent-based
  simulation models, because:
  – they are readily interperable in terms of them
  – the act of playing with a model over a period of
    time involves you in the model and its construction
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 13
The Tethered Goat




  In terms of ideas and assumptions, people are
like a tethered goat, they can wander a little way
       from what they were taught but not far
  Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 14
The Key Question (for this talk)


          What kinds of thing are usefully
                 communicated?

In other words, of all the knowledge-related
things one researcher has (e.g. ideas,
conceptual frameworks, models, proofs,
methodologies, data sets, case studies etc.)
what is worth telling other researchers about
(in presentations, papers etc.) and how?
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 15
The Sad Fact

Just because it is interesting and/or important
  to you, does not mean it will be to others

Or to put it in a positive light…
    Some things that are not useful and/or
   meaningful to persuade others about, are
vitally important to us individually and can be
 the powerhouse behind a creative academic
                      career
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 16
Part 2:

                            Personal Knowledge



Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 17
Polyani and Personal Knowledge

• Polanyi (1974)
• Some kinds of knowledge are not explicitly
  communicable…
• rather they are primarily passed on by doing
  things together…
• involving action, observation and a close
  feedback between people



  Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 18
Some Examples of Personal
Knowledge

• How to ride a bicycle
• What is socially acceptable at informal
  occasions
• In what circumstances to use particular kinds
  of language
• How to be a physicist/sociologist/biologist etc.
• How to talk
• What (most) words mean
• How to think
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 19
How to Simulate

• Although one can learn many supporting aspects of
  social simulation, such as
   –   What the commands mean
   –   How to run programs, make graphs
   –   How to analyse results
   –   Particular algorithms
• A lot that is crucial about simulation is learning by
  doing in a community of others, including:
   –   The style of doing social simulation
   –   What makes a good/interesting simulation
   –   How different simulation mechanisms work together
   –   How to relate/interpret simulation results to the
       observed world

   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 20
“Bridging Rules”

• Cartwright (1980)
• Makes a distinction between:
  – Explanatory Laws – why things happen
  – Phenomenological Laws – which literally fit the
    data
• And pointed out that often these were different
• For example the gas laws, and the atomic
  model of what is happening in a gas
• The connections between these were often left
  implicit, as defined by a community of practice,
  even in “mature” sciences – a kind of personal
  knowledge
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 21
“Bridging” in Social Simulation

• The details of the simulation run provides a possible
  “explanation” of the results but is very complex (which is
  the point of doing it!)
• The simulator will develop an intuition and rules of
  thumb…
• Which may be made explicit in terms of a hypothesis
  about how/why the simulation gives the results it does
• Some simulations concentrate on making this
  explanation as clear as possible but leave the
  connection with what is observed as an analogy
• Others concentrate on connecting the specification and
  results with evidence but leave any comprehensible
  explanation vague or implicit – e.g. only implied by
  graphs of results and textual description
• But really we need these linked, but this is rarely explicit
    Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 22
Conceptual Frameworks

• A set of inter-related ideas that a person (or
  occasionally a research group) uses to understand
  what is happening or what they are doing
• Can be the engine behind a stream of productive
  research
• But is basically personal, only transmittable by a
  longer-term interaction…
• And even then each person constructs their own
  version internally
• Which is important in terms of developing different
  approaches when the problem/environment
  changes
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 23
Part 3:

                                Public Knowledge



Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 24
Popper and Feyerabend

• Feyerabend (1975): It does not matter how
  one gets hypotheses (indeed one should
  not constrain this processes)
• Popper (1965): but these become publically
  useful (i.e. something akin to knowledge) if
  what is communicated is:
  1. Possible to show it is wrong (which includes
     being well sufficiently well-defined)
  2. and people have ample chance to do so

  Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 25
The Sociality of Precise Entities

• Precisely defined entities (simulations, data sets,
  hypotheses, proofs, algorithms) can be transmitted
  faithfully
• That is, they survive distant transmission without error
• This allows for a very social process in science, where
  different people can consider the same entities, which
  provide a precise common reference
• And (possibly) allow a collective exploration of variations
  of these (or uses of them)
• Which might result in a true evolution of these entities
• This does not mean that interpretations, discussions,
  understanding of these are not important…
• …but that these might change with fashions, needs,
  politics etc. over a shorter time frame

   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 26
Transmitting Ideas via Precise
Entities

• Often, the most effective way to get an idea
  accepted, is to transmit an associated precise
  entity, such as a simulation
• You cannot control how the associated ideas
  will be interpreted
• But at least this is re-interpreted from the
  precise entity each time by each person rather
  than being a re-interpretation of an
  interpretation of an… etc.
• The precise entities often persist long after the
  associated interpretations have lost potency
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 27
Part 4:

                           Some Complications



Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 28
Context

• Humans unconsciously and automatically
  learn to recognise/categorise kinds of
  situation and then preferentially allows
  access to memory based on this
• This means that what is relevant to a kind of
  situation automatically comes to mind and
  makes “foreground” conscious thought
  feasible
• (with the exception of socially instituted
  contexts) contexts are not usefully reifiable
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 29
A (simplistic) illustration of context from the
point of view of an actor




   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 30
Consequences of the Context-
Dependency of Human Thought
• Much academic explicit thought relies on the reliable,
  but implicit, co-recognition of the appropriate context
• Making as much of the context assumptions explicit as
  possible is an important part of being more scientific
• But it is impossible to do 100%
• Much social science keeps descriptions within context,
  maintaining its qualitative richness, but this is less
  “social” in terms of the collaborative processes of
  science
• Thinking from within different cognitive contexts is a
  creative and productive method
• But not itself usefully communicable (in possible
  contrast to the results of that thought)


   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 31
Thinking Analogically

• In an analogy the referential mappings to the domain of application are
  flexibly created in a creative fashion each time
• Thus there is a part (“the analogy”) that is applied to a different
  context, but…
• … its meaning (mapping of analogy to in-context references) is
  different each time it is applied
• We are so adapt at applying ideas in an analogical fashion that we are
  often unaware of the process
• The analogy may be transmitted in formal form (as a simulation or an
  explicit hypothesis)
• Analogies give an impression of generality because the form may be
  the same but, in fact, the mappings are different each time.
• This contrasts with “scientific” applications where what the different
  parts of the model refer to are specified explicitly
• Analogical thinking is powerful in developing personal understanding,
  but is different from actually modelling social phenomena
• Some simulations are used only as a computational analogy (e.g.
  evolution of cooperation)
    Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 32
Inseparability of Ideas and Message

• Quite a lot of separation between ideas and the way
  these are communicated, but this is never total.
• All communication does rely (eventually) on implicit
  shared understanding (e.g. natural language, how to
  make computational devices etc.) but, if this can be
  relied upon, then expressions using this can be
  effectively formal – such as an explicit hypothesis – and
  hence used to effectively communicate precise
  elements…
• ..but it also means that even precise entities carry with it
  implicit “flavours/conations/assumptions/messages”
• …and that the effective communication of one kind of
  entity often is facilitated by the communication of
  associated entities.

    Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 33
Part 5:

       Sharing Different Kinds of Things



Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 34
Simulation Models

• Simulation models are effectively not just
  the code of the simulation, but to be
  meaningful, need a cluster of other things
  – A set of results to help give an understanding of
    what the simulation does
  – Explicit hypotheses about it
  – A variety of descriptions at different levels
    about the simulation code
  – A description of how this simulation is currently
    being interpreted in terms the meaning of its
    parts in terms of what is being modelled
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 35
Theories

• Theories are not simple, despite the
  impression that might be given in papers
  etc. (Giere 1988)
• But rather, like simulations, have different
  aspects, including:
  – Its formal expression
  – exemplar precise formulations of this (models)
  – the meaning of its terms


   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 36
Data Sets

• These can be very persuasive but are not
  often shared
• There are now websites to do this with, but
  there are issues of confidentiality, license
  conditions etc.
• Helpful to be accompanied with descriptions
  of:
  –   Context of data
  –   Summaries of it, graphs tables
  –   An example of its use
  –   Maybe some hypotheses it seems to
      confirm/disconfirm

   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 37
Ideas

• Single ideas are somewhat difficult to
  transmit
• As explained, people are not open to new
  ideas, unless they provide added value in
  terms of making their thought systems more
  coherent or in terms of what it allows them
  to do
• Again, ideas travel better with precise
  exemplars
  Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 38
Conceptual Frameworks

• Trying to communicate a whole framework is
  very VERY difficult
• Not only because the elements of this rely on
  their relation to all the other elements and so is
  hard to communicate bit by bit
• It is hard to “think outside the box” from within
  such a framework and make your thoughts
  understandable by others
• Often explicit exemplars that come out of the
  framework are more effective “ambassadors”
  for the framework
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 39
Methodologies

• Almost always, a mixture of precise and
  implicit knowledge parts
• Similar to a conceptual framework, in that
  you have to “live” it, so that one learns it
  within a community that follows it, in
  addition to those parts that are explicitly
  described (statistics, SNA methods, etc.)
• Often what people do is primary and
  rationales of why are subsequent to this,
  which it makes difficult to “convert” others
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 40
Visions

• This is a general story, a motivating narrative
  that outlines what could come to pass
• This seems to “travel” relatively well as
  narratives seem to be innate in humans
• However these tend to be transitory and highly
  related to fashion in academic and funding
  circles
• Also one cannot control the interpretation of
  these narratives, once “released” they are out
  of your control
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 41
Part 6:

         Some Examples and Conclusion



Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 42
Axtell & Epstein’s Growing Artificial
Societies

• They had huge difficulty in getting their
  simulation work published in social science
  and economic journals
• The book was successful far more in terms of
  the simulations demonstrated than in the ideas
  in the book
• As a result of the exemplars of what (even
  simple) simulations could achieve this enabled
  an interest that sparked exploration of
  alternatives to analytic-dominated approaches
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 43
Axtell et al. Aligning Simulation Models

• Argued simple points – that replication is
  important but also surprisingly hard
• But persuasive in terms of a series of
  examples of actually doing it
• Motivation for others to do it is that it can
  allow the attack on the interpretation of
  simulation models by revealing hidden
  assumptions (as in Edmonds & Hales 2003)


   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 44
Deffuant, Amblard and Weisbuch
How Can Extremism Prevail?

• Showed a simple model, that others could
  easily re-implement and play with
• Had some explicit hypotheses
• And lots of results, with extensive
  illustration, exploration and analysis
• The intended interpretation only played a
  small part in this



  Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 45
Barreteau, Bousquet & Attonaty Role-
Playing Games for Opening the Black Box of
Multi-Agent Systems

• Is also illustrated with an extensive case
  study to convince that the approach is not
  only possible but enables researcher to do
  things not possible elsewhere
• Primarily cited as an exemplar of the
  participatory approach and of
  interdisciplinary research work
• Showed a new approach (to most) and
  what one can achieve using it
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 46
Edmonds and Moss KISS vs KIDS

• A conceptual paper…
• But, the “KIDS” idea was taken up as a
  label primarily by those that were already
  making complex evidence-based
  simulations
• Probably nobody who believes in simple
  (KISS) models was convinced
• The body of relevant KIDS simulations and
  their usefullness will ultimately determine its
  take up
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 47
Many “PhD” papers I review…

I don’t want to name these but many I see
tend to…
• Concentrate on what they did in terms of
   the specification of their simulations etc.
• Have a certain “zeal” in wanting to explain
   their personal conceptual framework
• Have a relative lack of results
Of course, many more mature researchers do
this too!
  Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 48
Conclusion

• The aim of this talk is to make you more aware
  of the impact of academic social life on your
  activities and research
• In particular, to motivate you to think about
  what you try to communicate in formal ways
  (theses, papers, conference presentations)
  and what can only come into play in extended
  interactions (discussions, collaborations) with
  others and as a personal treasure of ideas,
  intuitions etc.
• For example, telling others what you have
  done in great detail or trying to convince others
  of your personal conceptual framework
   Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 49
References
•   Axtell, R., R. Axelrod, et al. (1996). "Aligning Simulation Models: A Case Study and Results." Computational
    and Mathematical Organization Theory 1: 123-141.
•   Barreteau, B., Bousquet, F. and Attonaty, J-M. (2001) 'Role-Playing Games for Opening the Black Box of
    Multi-Agent Systems: Method and Lessons of Its Application to Senegal River Valley Irrigated Systems’,
    Journal of Artificial Societies and Social Simulation, 4(2):5 (http://jasss.soc.surrey.ac.uk/4/2/5.html)
•   Boyd and Richerson (1985) Culture and the evolutionary process, University of Chicago Press.
•   Cartwright, N. (1983) How the Laws of Physics Lie, Oxford University Press.
•   Deffuant, G. Amblard, F. and Weisbuch, G. (2002) How Can Extremism Prevail? a Study Based on the
    Relative Agreement Interaction Model, Journal of Artificial Societies and Social Simulation, 5(4):1
    (http://jasss.soc.surrey.ac.uk/5/4/1.html)
•   Edmonds, B. and Hales, D. (2003) Replication, Replication and Replication - Some Hard Lessons from
    Model Alignment. Journal of Artificial Societies and Social Simulation 6(4)
    (http://jasss.soc.surrey.ac.uk/6/4/11.html)
•   Edmonds, B. and Moss, S. (2005) From KISS to KIDS – an ‘anti-simplistic’ modelling approach. In P.
    Davidsson et al. (Eds.): Multi Agent Based Simulation 2004. Springer, Lecture Notes in Artificial Intelligence,
    3415:130–144. (http://cfpm.org/cpmrep132.html)
•   Epstein, J. M. and Axtell, R., (1996) Growing Artificial Societies: Social Science from the Bottom Up, MIT
    Press.
•   Feyerabend, P. (1975) Against Method. New Left Books.
•   Giere, R. (1988) Explaining Science: A Cognitive Approach. Chicago: University of Chicago Press.
•   Kuhn, T (1962) The Structure of Scientific Revolutions, University of Chicago Press.
•   Kummer, H., Daston, L., Gigerenzer, G., & Silk, J. (1997). The social intelligence hypothesis. In P. Weingart,
    P. Richerson, S. D. Mitchell & S. Maasen (Eds.), Human by nature: Between biology and the social
    sciences. Hillsdale, NJ: Erlbaum.
•   Polanyi, M. (1974) Personal Knowledge: Towards a Post-Critical Philosophy, University of Chicago Press.
•   Popper, K. R. (1979) Objective Knowledge: An Evolutionary Approach. Oxford University Press.
•   Reader, J. (1990) 'Man on Earth'. Penguin Books.
•   Thagard, P. (1989) Explanatory coherence, Behavioral and Brain Sciences, 12:435-502.


      Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 50
Ad. for a workshop 5/6 Sept!
                The End




         Bruce Edmonds
  http://bruce.edmonds.name
 Centre for Policy Modelling
          http://cfpm.org




Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 51

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Personal understanding and publically useful knowledge in Social Simulation

  • 1. Personal Understanding and Publically Useful Knowledge in Social Simulation Bruce Edmonds Centre for Policy Modelling, Manchester Metropolitan University Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 1
  • 2. Some “stylized facts” about PhD Students (and other new researchers) • They are very keen to tell people all the details of what they have done • They often come across some text/person which transforms their way of thinking • They often want to convince the world of their new conceptual framework or methodology • Their language can be very bound up with their “home” research group, sometimes to the extent that others find it hard to understand them Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 2
  • 3. This Talk will… • …attempt to explain why these occur • Point out some mistakes and confusions that some researchers make • To make a distinction between personal and “public” knowledge • Appreciate the value of non-communicable knowledge • To encourage you to think about what you communicate to other researchers and how • …and thus help you to have a greater impact in terms of reporting your research Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 3
  • 4. Outline of Talk 1. Introduction: Motivation and Some Preparatory Philosophy 2. Personal Knowledge 3. Public Knowledge 4. Some Complications 5. Sharing Different Kinds of Things 6. Some Examples Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 4
  • 5. Part 1: Motivation and Some Preparatory Philosophy Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 5
  • 6. 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 Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 6
  • 7. 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) Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 7
  • 8. SIH In academic life • Different communities of practice develop within different academic groups • There will be a core of (often implict) practices, styles, techniques, assumptions that define that group and hence are (pretty much) not alterable • Other items (often explict) will be the focus of debate within the community such as models, data sets, explicit hypotheses etc. Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 8
  • 9. Kuhn and scientific revolutions • Kuhn (1962) • Observed that science often progresses in terms of fairly sudden revolutions rather than via a gradual build up of knowledge • “Revolutionary science” involves a change in paradigm • In between revolutions: “normal science” • Effect of “theoretical spectacles” where data is selected dependent on paradigm • Different paradigms are incommensurable Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 9
  • 10. Example: Continental Drift • From Kuhn (1962) • That the earth’s crust was composed of huge “floating” plates that slowly moved was resisted by established researchers for a long time until the weight of evidence became overwhelming and a sufficient of (mostly younger) researchers had adopted this (Kuhn’s “revolutionary science”) • In contrast, ideas/results that are compatible with existing ideas can be incrementally added with relative ease (“normal science”) Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 10
  • 11. Explanatory Coherence • Thagard (1989) • People choose whether to believe something depending on how it would affect the coherency of the (augmented) network of (relevant) beliefs Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 11
  • 12. Growing an internal “Ecology” of Ideas • As the network of ideas, associations and knowledge grows and is pruned a stable structure appears • This is (usually) resistant to ideas that are incoherent with what is already there • Asking others to change whole parts of the structure is unlikely to be accepted easily • Ideas that strengthen the existing structure (giving it more coherence) are more likely to be accepted but only if it delivers a lot Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 12
  • 13. Theoretical Spectacles • Kuhn (1962): when we have adopted a theory we tend to filter what we see: – We notice aspects of data/observations that agree with it or are explained by it – We don’t notice (or explain away) anything that does not fit with the theory • We see the world “through” the present theory • This effect is even stronger with agent-based simulation models, because: – they are readily interperable in terms of them – the act of playing with a model over a period of time involves you in the model and its construction Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 13
  • 14. The Tethered Goat In terms of ideas and assumptions, people are like a tethered goat, they can wander a little way from what they were taught but not far Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 14
  • 15. The Key Question (for this talk) What kinds of thing are usefully communicated? In other words, of all the knowledge-related things one researcher has (e.g. ideas, conceptual frameworks, models, proofs, methodologies, data sets, case studies etc.) what is worth telling other researchers about (in presentations, papers etc.) and how? Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 15
  • 16. The Sad Fact Just because it is interesting and/or important to you, does not mean it will be to others Or to put it in a positive light… Some things that are not useful and/or meaningful to persuade others about, are vitally important to us individually and can be the powerhouse behind a creative academic career Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 16
  • 17. Part 2: Personal Knowledge Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 17
  • 18. Polyani and Personal Knowledge • Polanyi (1974) • Some kinds of knowledge are not explicitly communicable… • rather they are primarily passed on by doing things together… • involving action, observation and a close feedback between people Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 18
  • 19. Some Examples of Personal Knowledge • How to ride a bicycle • What is socially acceptable at informal occasions • In what circumstances to use particular kinds of language • How to be a physicist/sociologist/biologist etc. • How to talk • What (most) words mean • How to think Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 19
  • 20. How to Simulate • Although one can learn many supporting aspects of social simulation, such as – What the commands mean – How to run programs, make graphs – How to analyse results – Particular algorithms • A lot that is crucial about simulation is learning by doing in a community of others, including: – The style of doing social simulation – What makes a good/interesting simulation – How different simulation mechanisms work together – How to relate/interpret simulation results to the observed world Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 20
  • 21. “Bridging Rules” • Cartwright (1980) • Makes a distinction between: – Explanatory Laws – why things happen – Phenomenological Laws – which literally fit the data • And pointed out that often these were different • For example the gas laws, and the atomic model of what is happening in a gas • The connections between these were often left implicit, as defined by a community of practice, even in “mature” sciences – a kind of personal knowledge Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 21
  • 22. “Bridging” in Social Simulation • The details of the simulation run provides a possible “explanation” of the results but is very complex (which is the point of doing it!) • The simulator will develop an intuition and rules of thumb… • Which may be made explicit in terms of a hypothesis about how/why the simulation gives the results it does • Some simulations concentrate on making this explanation as clear as possible but leave the connection with what is observed as an analogy • Others concentrate on connecting the specification and results with evidence but leave any comprehensible explanation vague or implicit – e.g. only implied by graphs of results and textual description • But really we need these linked, but this is rarely explicit Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 22
  • 23. Conceptual Frameworks • A set of inter-related ideas that a person (or occasionally a research group) uses to understand what is happening or what they are doing • Can be the engine behind a stream of productive research • But is basically personal, only transmittable by a longer-term interaction… • And even then each person constructs their own version internally • Which is important in terms of developing different approaches when the problem/environment changes Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 23
  • 24. Part 3: Public Knowledge Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 24
  • 25. Popper and Feyerabend • Feyerabend (1975): It does not matter how one gets hypotheses (indeed one should not constrain this processes) • Popper (1965): but these become publically useful (i.e. something akin to knowledge) if what is communicated is: 1. Possible to show it is wrong (which includes being well sufficiently well-defined) 2. and people have ample chance to do so Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 25
  • 26. The Sociality of Precise Entities • Precisely defined entities (simulations, data sets, hypotheses, proofs, algorithms) can be transmitted faithfully • That is, they survive distant transmission without error • This allows for a very social process in science, where different people can consider the same entities, which provide a precise common reference • And (possibly) allow a collective exploration of variations of these (or uses of them) • Which might result in a true evolution of these entities • This does not mean that interpretations, discussions, understanding of these are not important… • …but that these might change with fashions, needs, politics etc. over a shorter time frame Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 26
  • 27. Transmitting Ideas via Precise Entities • Often, the most effective way to get an idea accepted, is to transmit an associated precise entity, such as a simulation • You cannot control how the associated ideas will be interpreted • But at least this is re-interpreted from the precise entity each time by each person rather than being a re-interpretation of an interpretation of an… etc. • The precise entities often persist long after the associated interpretations have lost potency Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 27
  • 28. Part 4: Some Complications Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 28
  • 29. Context • Humans unconsciously and automatically learn to recognise/categorise kinds of situation and then preferentially allows access to memory based on this • This means that what is relevant to a kind of situation automatically comes to mind and makes “foreground” conscious thought feasible • (with the exception of socially instituted contexts) contexts are not usefully reifiable Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 29
  • 30. A (simplistic) illustration of context from the point of view of an actor Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 30
  • 31. Consequences of the Context- Dependency of Human Thought • Much academic explicit thought relies on the reliable, but implicit, co-recognition of the appropriate context • Making as much of the context assumptions explicit as possible is an important part of being more scientific • But it is impossible to do 100% • Much social science keeps descriptions within context, maintaining its qualitative richness, but this is less “social” in terms of the collaborative processes of science • Thinking from within different cognitive contexts is a creative and productive method • But not itself usefully communicable (in possible contrast to the results of that thought) Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 31
  • 32. Thinking Analogically • In an analogy the referential mappings to the domain of application are flexibly created in a creative fashion each time • Thus there is a part (“the analogy”) that is applied to a different context, but… • … its meaning (mapping of analogy to in-context references) is different each time it is applied • We are so adapt at applying ideas in an analogical fashion that we are often unaware of the process • The analogy may be transmitted in formal form (as a simulation or an explicit hypothesis) • Analogies give an impression of generality because the form may be the same but, in fact, the mappings are different each time. • This contrasts with “scientific” applications where what the different parts of the model refer to are specified explicitly • Analogical thinking is powerful in developing personal understanding, but is different from actually modelling social phenomena • Some simulations are used only as a computational analogy (e.g. evolution of cooperation) Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 32
  • 33. Inseparability of Ideas and Message • Quite a lot of separation between ideas and the way these are communicated, but this is never total. • All communication does rely (eventually) on implicit shared understanding (e.g. natural language, how to make computational devices etc.) but, if this can be relied upon, then expressions using this can be effectively formal – such as an explicit hypothesis – and hence used to effectively communicate precise elements… • ..but it also means that even precise entities carry with it implicit “flavours/conations/assumptions/messages” • …and that the effective communication of one kind of entity often is facilitated by the communication of associated entities. Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 33
  • 34. Part 5: Sharing Different Kinds of Things Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 34
  • 35. Simulation Models • Simulation models are effectively not just the code of the simulation, but to be meaningful, need a cluster of other things – A set of results to help give an understanding of what the simulation does – Explicit hypotheses about it – A variety of descriptions at different levels about the simulation code – A description of how this simulation is currently being interpreted in terms the meaning of its parts in terms of what is being modelled Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 35
  • 36. Theories • Theories are not simple, despite the impression that might be given in papers etc. (Giere 1988) • But rather, like simulations, have different aspects, including: – Its formal expression – exemplar precise formulations of this (models) – the meaning of its terms Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 36
  • 37. Data Sets • These can be very persuasive but are not often shared • There are now websites to do this with, but there are issues of confidentiality, license conditions etc. • Helpful to be accompanied with descriptions of: – Context of data – Summaries of it, graphs tables – An example of its use – Maybe some hypotheses it seems to confirm/disconfirm Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 37
  • 38. Ideas • Single ideas are somewhat difficult to transmit • As explained, people are not open to new ideas, unless they provide added value in terms of making their thought systems more coherent or in terms of what it allows them to do • Again, ideas travel better with precise exemplars Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 38
  • 39. Conceptual Frameworks • Trying to communicate a whole framework is very VERY difficult • Not only because the elements of this rely on their relation to all the other elements and so is hard to communicate bit by bit • It is hard to “think outside the box” from within such a framework and make your thoughts understandable by others • Often explicit exemplars that come out of the framework are more effective “ambassadors” for the framework Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 39
  • 40. Methodologies • Almost always, a mixture of precise and implicit knowledge parts • Similar to a conceptual framework, in that you have to “live” it, so that one learns it within a community that follows it, in addition to those parts that are explicitly described (statistics, SNA methods, etc.) • Often what people do is primary and rationales of why are subsequent to this, which it makes difficult to “convert” others Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 40
  • 41. Visions • This is a general story, a motivating narrative that outlines what could come to pass • This seems to “travel” relatively well as narratives seem to be innate in humans • However these tend to be transitory and highly related to fashion in academic and funding circles • Also one cannot control the interpretation of these narratives, once “released” they are out of your control Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 41
  • 42. Part 6: Some Examples and Conclusion Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 42
  • 43. Axtell & Epstein’s Growing Artificial Societies • They had huge difficulty in getting their simulation work published in social science and economic journals • The book was successful far more in terms of the simulations demonstrated than in the ideas in the book • As a result of the exemplars of what (even simple) simulations could achieve this enabled an interest that sparked exploration of alternatives to analytic-dominated approaches Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 43
  • 44. Axtell et al. Aligning Simulation Models • Argued simple points – that replication is important but also surprisingly hard • But persuasive in terms of a series of examples of actually doing it • Motivation for others to do it is that it can allow the attack on the interpretation of simulation models by revealing hidden assumptions (as in Edmonds & Hales 2003) Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 44
  • 45. Deffuant, Amblard and Weisbuch How Can Extremism Prevail? • Showed a simple model, that others could easily re-implement and play with • Had some explicit hypotheses • And lots of results, with extensive illustration, exploration and analysis • The intended interpretation only played a small part in this Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 45
  • 46. Barreteau, Bousquet & Attonaty Role- Playing Games for Opening the Black Box of Multi-Agent Systems • Is also illustrated with an extensive case study to convince that the approach is not only possible but enables researcher to do things not possible elsewhere • Primarily cited as an exemplar of the participatory approach and of interdisciplinary research work • Showed a new approach (to most) and what one can achieve using it Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 46
  • 47. Edmonds and Moss KISS vs KIDS • A conceptual paper… • But, the “KIDS” idea was taken up as a label primarily by those that were already making complex evidence-based simulations • Probably nobody who believes in simple (KISS) models was convinced • The body of relevant KIDS simulations and their usefullness will ultimately determine its take up Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 47
  • 48. Many “PhD” papers I review… I don’t want to name these but many I see tend to… • Concentrate on what they did in terms of the specification of their simulations etc. • Have a certain “zeal” in wanting to explain their personal conceptual framework • Have a relative lack of results Of course, many more mature researchers do this too! Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 48
  • 49. Conclusion • The aim of this talk is to make you more aware of the impact of academic social life on your activities and research • In particular, to motivate you to think about what you try to communicate in formal ways (theses, papers, conference presentations) and what can only come into play in extended interactions (discussions, collaborations) with others and as a personal treasure of ideas, intuitions etc. • For example, telling others what you have done in great detail or trying to convince others of your personal conceptual framework Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 49
  • 50. References • Axtell, R., R. Axelrod, et al. (1996). "Aligning Simulation Models: A Case Study and Results." Computational and Mathematical Organization Theory 1: 123-141. • Barreteau, B., Bousquet, F. and Attonaty, J-M. (2001) 'Role-Playing Games for Opening the Black Box of Multi-Agent Systems: Method and Lessons of Its Application to Senegal River Valley Irrigated Systems’, Journal of Artificial Societies and Social Simulation, 4(2):5 (http://jasss.soc.surrey.ac.uk/4/2/5.html) • Boyd and Richerson (1985) Culture and the evolutionary process, University of Chicago Press. • Cartwright, N. (1983) How the Laws of Physics Lie, Oxford University Press. • Deffuant, G. Amblard, F. and Weisbuch, G. (2002) How Can Extremism Prevail? a Study Based on the Relative Agreement Interaction Model, Journal of Artificial Societies and Social Simulation, 5(4):1 (http://jasss.soc.surrey.ac.uk/5/4/1.html) • Edmonds, B. and Hales, D. (2003) Replication, Replication and Replication - Some Hard Lessons from Model Alignment. Journal of Artificial Societies and Social Simulation 6(4) (http://jasss.soc.surrey.ac.uk/6/4/11.html) • Edmonds, B. and Moss, S. (2005) From KISS to KIDS – an ‘anti-simplistic’ modelling approach. In P. Davidsson et al. (Eds.): Multi Agent Based Simulation 2004. Springer, Lecture Notes in Artificial Intelligence, 3415:130–144. (http://cfpm.org/cpmrep132.html) • Epstein, J. M. and Axtell, R., (1996) Growing Artificial Societies: Social Science from the Bottom Up, MIT Press. • Feyerabend, P. (1975) Against Method. New Left Books. • Giere, R. (1988) Explaining Science: A Cognitive Approach. Chicago: University of Chicago Press. • Kuhn, T (1962) The Structure of Scientific Revolutions, University of Chicago Press. • Kummer, H., Daston, L., Gigerenzer, G., & Silk, J. (1997). The social intelligence hypothesis. In P. Weingart, P. Richerson, S. D. Mitchell & S. Maasen (Eds.), Human by nature: Between biology and the social sciences. Hillsdale, NJ: Erlbaum. • Polanyi, M. (1974) Personal Knowledge: Towards a Post-Critical Philosophy, University of Chicago Press. • Popper, K. R. (1979) Objective Knowledge: An Evolutionary Approach. Oxford University Press. • Reader, J. (1990) 'Man on Earth'. Penguin Books. • Thagard, P. (1989) Explanatory coherence, Behavioral and Brain Sciences, 12:435-502. Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 50
  • 51. Ad. for a workshop 5/6 Sept! The End Bruce Edmonds http://bruce.edmonds.name Centre for Policy Modelling http://cfpm.org Personal Understanding and Publically Useful Knowledge in Social Simulation, Bruce Edmonds, ESSA Sum Sch, Toulouse, July 2012, slide 51

Editor's Notes

  1. Imagine a professor of physics in a wild place – does his intelligence help him to survive?
  2. Reader 1980, Man on Earth