1. Paul Devine & Rahul Savani
AGENT BASED MODELLING
Paul Devine
&
Rahul Savani

2. Introduction What is Agent-Based Modelling? Why do it?
How do you do it?

3. What is Agent Based Modelling?
Simulation Approach
Built up from the component parts of a system
System behaviour emerges from fundamental features
Agents
Autonomous
Heterogeneous
Have relationships
Exhibit behaviours & make decisions

4. Why Model This Way? Real systems are often Intuitive
Complex
Comprised of many interacting entities
Affected by individual differences
Intuitive
A different perspective
Agents can represent
People, organisms, organisations etc.

5. How Do We Build the Model?
(Live)
Data
Novel
Investigation
Run
Analyse
&
Revise
Understand
the
Target System
Data
Analysis
Build
Model
Output
Domain
Expertise

6. Apply this to the Movie Market
The problem
Forecast movie box office
10 week rolling forecast
Across the whole market
Why agent based modelling?
Existing approaches had reached a limit
To capture the social aspects of movie-going

7. Building the Model Domain Experts Data Novel Investigation
Film execs, marketing execs etc. Us
Data
Historical, survey
Novel Investigation
Data visualisation, behavioural study

8. Summary Decompose the System Identify Agents Build Attributes
Behaviours
Interactions
Build
Incremental
Validate and verify