a model of making

A Model of Making, Bruce Edmonds, Centre for Policy Modelling, DiDIY Meeting Thessalonika, Feb. 2016. slide 1

A Model of Making- A framework for representing, exploring and

integrating Digital DIY issues & processes

Bruce EdmondsCentre for Policy Modelling

Manchester Metropolitan University


WP7 Strategy

Is in two parts:1. Using Simulation Models (T7.1 MMU)

– Develop an framework to support model development– Currently this is abstract but flexible– We want your input/participation to develop these into

a series of models that address more specific issues and (maybe) to more reflect particular case studies

– This process will inform a wider integration of ideas2. Other Integration (T7.2 UoW; T7.3 Abacus;

T7.4 FKI). May be informed by results of T7.1 but start in M18. Proposals as to how to do these will be made/discussed at July 2016 meeting.


Purpose of this session, to…

1. tell you what we have been up to2. explain and illustrate the modelling framework

we have produced and give you an idea as to what it can do, its potential

3. give you a chance to ask questions about it4. get critique/comments/suggestions about it5. collect ideas as to which directions we will

develop models from this6. form “user groups” of those interested in helping

advise/direct/critique/validate particular models


Motivation

Digital DIY involve complex phenomena, involving a mix of many dimensions, including:• micro-level and macro-level• conditions and outcomes• individual concerns and societal issues• processes and structures• things, their electronic representations and how

people think about both of these• formal plans/designs/etc. and informal stories• the built-in and the emergent


Modelling Goals

• To develop a modelling framework that will facilitate the construction of simulations that capture Digital DIY issues and scenarios

• To go to the nub – to explicitly represent the process of making things, including sharing our representations of those objects, teaching others how to make them, trading them etc.

• Thus to produce integrated representations of our many ideas within complex and dynamic simulations to make analysis & reference more explicit

• To enable the exploration of a variety of “what if” questions concerning making and sharing


The Technique: Agent-Based Modelling

Allows a more straightforward reality ↔ representation, individual people are represented by individual agents and individual objects by individual simulation objects.• Heterogeneity is no problem, every object can have different

characteristics and every agent behave differently (simulation anarchy rules )

• Consequences can emerge from the complicated interactions of agents within the simulation, these outcomes are not ‘built in’

• We can integrate and deal with the different ‘dimensions’ just listed within a single (but complex) ABM, which can then be experimented upon, displayed, inspected etc.

• Can range from quite abstract (as ATM) to more specific to observed situations/data


The Simulation Platform/Code

Is mostly written in NetLogo, which is:• freely available and usable• relatively easy to understand and use• is completely open source (in Java/Scala)• there are now several active sites for sharing

models (e.g. modelling commons, OpenABM)It uses some extensions to NetLogo which are also: freely available, with open source code, written in Java or Scala, open to code forks and feedback

Code and docs at: http://openabm.org/model/4871


The String MakerWorld

• Things in this model are strings, e.g. ‘ACC&BA’• They are made form a finite number of ‘elements’ {A,

B, C…} and the two special symbols: {&, >}• Only certain strings can be extracted from the

environment (randomly determined at the start). All other strings have to be made from these.

• Only certain target strings can have inherent value (randomly determined at the start). These can be ‘used’ to get that value

• Strings can be joined/split by hand at & but to get any other kind of longer string you have to use a tool (another string with “>” in it that can change strings)


Simple Example

Say an agent was in the following situation:Available in environment: A; A>; AA; AB; B>; BA; BB; A&A; A&B; AAA; AB>BAHas use value to agent: AB; A&B; AAA; AAB; ABA; B&A; BBA; BBB; A&AA

Possible sequences of actions by agent:• Get A&B then immediately use it• Get A and BA then join these to make A&BA• Get A&B, split this into A and B, then join these to

make B&A and use this• Get AB use tool AB>BA on it to make BA, use it


Motivation behind String MakerWorld

• Simplest world that allows the complexity of making to be explicitly represented

• Working out how to make valuable strings is hard, which gives value to good plans (and hence motivation for trading/sharing plans)

• Control over which resources each agent has access to can add heterogeneity in production

• Control over the target strings each agent can directly use can add heterogeneity of need

• Heterogeneity of resources and needs gives motivation for the trade/sharing of objects


The Model

• Agents are patches but can interact in any pattern they choose/learn

• Things are explicitly tracked with their own properties (which matter structurally)

Agents are implemented as patches

Object and its string owned by an agent

Some objects are complex, this one soft-

joined from smaller parts

Some objects are simple, this one composed of a single

“element”

This object is a tool, in this case adding a soft

join into the string (allowing it to be maybe

separated later)The arrow indicates a sale/transfer of an object

from one agent to another


Plans

• Plans (the sequence of actions needed to make particular things) are separate from the things

• Agents sometimes do things experimentally (ATM at random) to see what they can make

• Agents remember how they made things in terms of plans – the actions necessary to get any particular outcome

• Agents remember the better value plans and preferentially execute those again

• These plans could be sent/shared/licensed between agents


Some example plans learnt by an agent

value 3.25: realise [BAA split-right [B&BAA get]]value 1.5: sell [B get] (patch 0 0)value 1.25: realise [BAA split-right [B&BAA split-right [B&B&BAA join [B split-left [B&BAA get]] [B&BAA get]]]]value 1.25: sell [B split-left [B&BAA get]] (patch 2 0)value -1: join-randomvalue -1.5: B split-left [B&BAA get]value -2: get-random

• Note that alternative plans to make the same things might be remembered, but with different costs

• Plans can be arbitrarily complex, thought each action has a small cost associated with it, so more complex plans will tend to have lower values (unless they result in a more valuable result)

• Agents prefer to re-use plans with higher value


The (current) main simulation loop

Continually (each tick), agent:Considers a number of plans (including the default random ones) with a bias towards more valuable ones:Until one works:

Assess next plan to see if it would workIf so, do plan!If new, compile and remember plan

If have too many plans in memory, maybe forget one (with a bias towards the less valuable ones)


Number of realised items used for different lengthed targets


Average Wealth in Some Example Runs


Spread of Wealth for the same runs


Statistics concerning a single, example run


Things we might add into the model

The structure of the model has been designed to make it easy to add a variety of processes/innovations/affordances, for example:1. The sharing or communicating of plans2. Different strategies for deciding what to do3. Introduction of ‘1D string printers’ that can make any

string (but only with certain elements)4. The ‘instantiation’ of plans into manufacturing

facilities (with high capital costs but then low production costs and high production levels)

5. Different kinds of market, for agents to sell to each other


Issues we might explore…

…include:• Changing the heterogeneity of needs, from

everybody has similar needs, to all different• Explore the conditions under which more centralised

manufacturing or markets emerge• Explore the impact of introducing new technology

(something equivalent to 3D printers)• Looking at how the structure of communication (for

plans or selling/sharing items) effects things• Maybe even wilder topics, e.g.

– what if all objects contain their own plans– or come with tools to disassemble/reassemble/fix it


The End!

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

These slides available at: http://slideshare.net/BruceEdmonds

The model code and its documentation freely available at: http://openabm.org/model/4871

a model of making

Education