4. ABM in a nutshell
AGENT
ENVIRONMENT
SENSORS
MESSAGES
ACTIONS
PERCEPTS
OBJECT
ACTUATORS
Based&on&Bordini&et&al&&(2007)
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5. Why are we talking about ABM?
• It shows promise for
understanding complex
systems:
– heterogeneous and
adaptive actors
– complex interactions:
interdependencies;
feedback loops
– dynamic environment
• It provides an accessible
metaphor for modelling
– modelling individuals
• More and more data is
available for our models
- Finer levels of
granularity
• Computing power is
available on-demand
- Costs continue to
reduce
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6. Classic ABM: Schelling Segregation Model
• Developed by Thomas Schelling in 1970s.
• Study racial segregation of populations emerging
from individual discriminatory behaviours.
Thursday, 30 May 13
13. QuitSIM Behaviour Tree
Take up
smoking?
Never smoker = 1
Become smoker
Age, gender
Do nothing
Cut down
attempt length, route,
age, dependency
Consume
media / ingest
experience
Smoker
Smoker = 1
Never Smoker
Never Smoker = 1
Consume
media / ingest
experience
Get support?
Set support flag
Planned or
Unplanned?
Do something
about
smoking?
motivation, events,
price, GP, social,
pregnant, media,
random
8#2013
Thursday, 30 May 13
14. Technical Challenges
BUILD VALIDATE EXPERIMENT
Designing*and
building*models
Building
Confidence*
in*Models
Conducting
Large?Scale
Experiments
HARD VERY,*VERY*HARD VERY*HARD
Thursday, 30 May 13
30. Further study
Book:
• John Miller and Scott Page: 'Complex Adaptive
Systems: An Introduction to Computational Models
of Social Life' (2007)
Coursera:
• Scott Page: 'Model Thinking'
• https://www.coursera.org/course/modelthinking
Thursday, 30 May 13