Participatory simulations for developing scenarios in environmental resource management

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Participatory simulations for developing
scenarios in environmental resource management
The FIRMA Project is supported by European
Union's Framework 5 Programme for Research and
Development, and by the European Commission as
part of its Key Action on Sustainable Management
and Quality of Water programme (contract
EVK1-CT1999-00016)

• Nigel Gilbert, Sarah Maltby
• Tasia Asakawa
• University of Surrey

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Policy and applied research

• Inform
• Inspire
• Influence
• Develop
• Encourage

Decision-makers (policymakers)
Communities
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Academic social science context

• Scepticism about the possibility of prediction
• Theoretical abstraction important but application
  difficult
• Increased demands for relevance and application

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A new(ish) approach

• Since the 1960s
• Interactive social science
• Participatory methods
• Action research
• In all these
• Stakeholders learn from their peers as well as
  from social scientists
• Academics are also stakeholders
• Praxis
• Tacit as well as formalised knowledge about
  action and its consequences

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Interactive or participatory social science

• Users and beneficiaries in collaboration with
  academics
• Participatory methods have been advocated as a
  way of
• Empowering the disadvantaged
• Involving the powerful
• Reducing the distance between academic and lay
  discourse

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Advantages

• Brings different perspectives
• Brings different kinds of knowledge
• Lay knowledge
• Expert knowledge
• Academic knowledge
• Identifies crucial problems
• Stakeholders have some ownership of results

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Problems

• Representation of distributed stakeholders
• E.g. the public
• Dealing with conflict between stakeholders
• Confidentiality and privacy
• Maintaining the motivation of participants

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Agent-based social simulation

• Stakeholders are represented in the model as
  agents
• The agents have the goals, beliefs, and
  capabilities of the real stakeholders (or some
  simplified version of these)
• Then let the model run to see what happens
• In order to develop scenarios, spot recurrent
  patterns of action, identify unanticipated
  consequences

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But

• At best, stakeholders can have a Gods eye view
  of the model, observing its outputs, while what
  they want is to understand the setting from their
  own perspective
• Hence stakeholders either have to do some
  translation or (perhaps more likely) they just
  ignore the model because the translation is too
  difficult.
• The model doesnt give them much help with an
  intuitive understanding of the dynamics

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Putting the user in the model

• An alternative is to replace some or even all of
  the agents by real stakeholders (or their
  representatives)
• The model becomes a multi-user strategy
  simulation
• Analogous to single person vs. multi-player
  computer games

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Advantages

• More engaging for the users
• More realistic
• Instead of looking down on the model, the
  player participates in a virtual setting
• Users can treat the simulation like a flight
  simulator
• Practice in circumstances that would be dangerous
  if carried out in real life
• Scenarios can be established in the simulation as
  starting points and then users see what happens
  from there

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More advantages

• Conflict between stakeholders can be observed
  and/or modelled
• Can provide data for researchers on what people
  would do
• Elicits tacit knowledge
• Not just what they say they would do
• And on how they react to others actions that are
  in response to their actions (etc.)

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Distributed multi-user models

• Participants can be anywhere, provided that they
  have internet access
• E.g. in their office
• No duration restrictions
• Can be involved while doing their ordinary work
• But
• Less motivation without face-to-face interaction
• Technical difficulties less easy to solve
• Requires internet access

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Implementation options

• Client-side
• Needs to run on many differently configured PCs
• Java, Javascript
• Inter-player communication hard to implement and
  control
• OR
• Server side
• All software runs on a central server
• Server generates HTML pages dynamically
• Client only needs a standard web browser
• Inter-player communication is simple to implement

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Server side implementation

• Apache web server
• Standard web server
• PHP
• Scripting language
• All normal programming constructs
• Basic object orientated features
• Good interfaces to other software and libraries
• Relational database
• PostgreSQL
• MySQL
• TCP/IP or other inter-process communication to
  other models
• All this is open source, free and available under
  the GNU licence

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The server
Program
Apache Web Server
PHP module
Page request
HTML
Data Read/write
Web page
PostgreSQL database
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Sample PHP
PHP programming language similar to C
lt?php function show_scale(val) / display a
bar to show value of val / valround(val)
if (val gt 10) val 10 if (val lt 0 ) val
0 colour (val gt 5 ? 'grn'
'red') echo "lttdgtltimg SRC\"images/bar-colour-
val.jpg\" ALT\"Valueval\" width104
height14gtlt/tdgt\n" ?gt
Embedded HTML
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Interface between PHP and the database
n_msgs 3 / get the last 3 public
messages / query new query("SELECT id,
sender, recipient, to_char(timesent,
'HH24MI on DD Mon') as senttime,
timeread, msg
FROM msgs WHERE
(recipient 'All')
ORDER BY timesent DESC LIMIT n_msgs")
display_msgs(query)
SQL statement sent to database
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The context

• Drought in summer 1976 led to shock to Zurichs
  water supply system
• Capacity increased to guarantee a secure supply
• But over-supply leads to risk of stagnant water
• Water demand has since fallen as a result of
  water saving technology and changing business
  behaviour
• Water utility regarded as inefficient due to high
  fixed costs
• Demand management through pricing would allow
  parts of the system to be closed
• But tariffs ultimately controlled by public
  through referenda

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Playing the game design choices

• Roles
• Stakeholder representatives play their own roles
• They bring their own knowledge to game
• Stakeholders play other roles
• Not tied to prior positions and strategies
• Time
• Real-time
• Too slow!
• Game time
• Player events drive time forwards
• Simulated Clock time

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Computational agents

• The model can include computational agents as
  well as real players (people)
• When real players are absent (on holiday, away
  from the office,)
• When real players have not or cannot be recruited
• Test of modelling adequacy Can they be
  distinguished by their actions from real players?
• If all players are agents, game reverts to being
  a conventional multi-agent simulation

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Evaluating the model

• Robustness
• Yields policy advice that applies in a range of
  scenarios
• Transparency
• Model is understandable to stakeholders
• Evaluating the process
• Is it used?
• Is effect lasting?
• Has learning occurred?

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Summary

• Computational models can be used for discovery or
  for policy
• And possibly for both at the same time
• If they are to be used for policy, their use must
  be carefully designed with an understanding of
  the policy context
• That context consists of people with many
  different pressures, goals, experiences and
  interests
• And often situations of deep-rooted conflict and
  power differences

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Participatory methods and simulation

• Multi-agent simulations can profitably be used as
  a component of participatory methods, with some
  agents being computational and others human
• The design of the simulation will help to recover
  and formalise the knowledge of the participants
• The use of the simulation will help to educate
  the participants about options and consequences
  of action
• The method recognises (as many participatory
  methods do not) the inherent conflict in many
  settings

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