Participatory simulations for developing scenarios in environmental resource

managementNigel Gilbert, Sarah Maltby

Tasia AsakawaUniversity of Surrey

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)

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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 ‘God’s 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 doesn’t 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

Apache WebServer

PHPmodule

PostgreSQLdatabase

Pagerequest

Program

DataRead/write

HTML

Web page

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Sample PHP

<?php

function show_scale($val) {/* display a bar to show value of $val */

$val=round($val);if ($val > 10) $val = 10;if ($val < 0 ) $val = 0;$colour = ($val >= 5 ? 'grn' : 'red');echo "<td><img SRC=\"images/bar-$colour-$val.jpg\"

ALT=\"Value=$val\" width=104 height=14></td>\n";

}

?>

PHP: programming language

similar to C++

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, 'HH24:MI 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 Zurich’s 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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