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Agent-Based Modelling
TECHNIQUES IN GEOGRAPHIC DATA SCIENCE
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
What is Agent-Based Modelling? (1)
"An agent-based model (ABM) is a class of computational models for simulating the actions and
interactions of autonomous agents with a view to assessing their effects on the system as a
whole.“
Combines elements of:
- game theory,
- complex systems,
- emergence,
- computational sociology,
- multi-agent systems,
- evolutionary programming.
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
What is Agent-Based Modelling? (2)
Most agent-based models are composed of:
(1) numerous agents
(2) decision-making heuristics;
(3) learning rules or adaptive processes;
(4) an interaction topology; and
(5) an environment.
ABMs are typically implemented as computer simulations, either as custom software,
or via ABM toolkits, and this software can be then used to test how changes in individual
behaviors will affect the system's emerging overall behavior.
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
Early Developments:
John Conway’s ‘Game of Life’
Rules
1. Any live cell with fewer than two live
neighbours dies, as if by underpopulation.
2. Any live cell with two or three live
neighbours lives on to the next generation.
3. Any live cell with more than three live
neighbours dies, as if by overpopulation.
4. Any dead cell with exactly three live
neighbours becomes a live cell, as if by
reproduction.
Thomas Schelling (1969). Models of Segregation.
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
"Imagine a line along which blacks and whites have been distributed in equal numbers and
random order...
Define everybody's 'neighbourhood' as extending four neighbours on either side, and suppose
that everyone is content if half his 'neighbours' are the same color as he.
If fewer than half are his color, he moves in either direction to the nearest point at which half his
eight nearest neighbors are the same color as he."
Thomas Schelling (1969). Models of Segregation.
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
"I have put a dot over the individuals that are dissatisfied...
Suppose that the dotted individuals move in turn, starting from the left, if they are still
discontent when their turns come: rearrange the plusses and zeroes by moving each dotted one
to the nearest point where, inserting itself between two others, at least four of its eight
neighbors are of its own color.”
Thomas Schelling (1969). Models of Segregation.
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
"Eight have become newly discontent. We give them their turn and... we end up with six groups
of alternating color.
All of this is too abstract to be a motion picture of whites and blacks or boys and girls choosing
houses on a road... but it is suggestive of some of the dynamics that could be present in
individually motivated segregation"
Axelrod & Hamilton (1981).
The Evolution of Cooperation.
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
Axelrod & Hamilton (1981).
The Evolution of Cooperation.
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
"With two individuals destined never to meet again, the only strategy that can be called a
solution to the game is to defect always...
[But] If an individual can recognize a previous interactant and remember some aspects of the
prior outcomes, then the strategic situation becomes an integrated Prisoner's Dilemma with a
much richer set of possibilities."
"[Axelrod] conducted a computer tournament for the Prisoner's Dilemma... [There was] a game
length of 200 moves. The 14 entries and a totally random strategy were paired with each other
in a round robin tournament... the result of the tournament was that the highest average score
was attained by the simplest of all strategies submitted: TIT FOR TAT. This strategy is simply one
of cooperating on the first move and then doing whatever the other player did on the preceding
move. Thus TIT FOR TAT is a strategy of cooperation based on reciprocity."
ABM became widespread in the 1990s
- Disease Dynamics in a Refugee Camp
- Modelling the Emergence of Riots
- Exploring the Growth of Slums
- The Spread of Agriculture during the Neolithic Period
Crooks, Malleson et al. (2018). Agent-Based Modelling and Geographical Information Systems.
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
Critique
- Ontology
Livet, Phan & Sanders (2008). Why do we need Ontology for Agent-Based Models.
'the question of the ontological compatibility between the “model world” and the “real world.’
- Causal Explanation
Grune-Yanoff (2008). The explanatory potential of artificial societies.
'... models do not provide potential causal explanations. Instead... they provide potential
functional explanations.'
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
Simple Example:
Rabbit Population
Growth
https://github.com/peterprescott/agent-based-modelling
Simple ABM: Create Environment
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
Simple ABM: Define Agent
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
Simple ABM: Define Agent Behaviour
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
Simple ABM: Define a Rabbit
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
Simple ABM: Define Rabbit Behaviour (1)
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
Simple ABM: Define Rabbit Behaviour (2)
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
Simple ABM: Define Rabbit Behaviour (3)
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
Simple ABM: Extend Model…
PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.

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A Brief Introduction to Agent-Based Modelling

  • 1. Agent-Based Modelling TECHNIQUES IN GEOGRAPHIC DATA SCIENCE PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 2. What is Agent-Based Modelling? (1) "An agent-based model (ABM) is a class of computational models for simulating the actions and interactions of autonomous agents with a view to assessing their effects on the system as a whole.“ Combines elements of: - game theory, - complex systems, - emergence, - computational sociology, - multi-agent systems, - evolutionary programming. PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 3. What is Agent-Based Modelling? (2) Most agent-based models are composed of: (1) numerous agents (2) decision-making heuristics; (3) learning rules or adaptive processes; (4) an interaction topology; and (5) an environment. ABMs are typically implemented as computer simulations, either as custom software, or via ABM toolkits, and this software can be then used to test how changes in individual behaviors will affect the system's emerging overall behavior. PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 4. Early Developments: John Conway’s ‘Game of Life’ Rules 1. Any live cell with fewer than two live neighbours dies, as if by underpopulation. 2. Any live cell with two or three live neighbours lives on to the next generation. 3. Any live cell with more than three live neighbours dies, as if by overpopulation. 4. Any dead cell with exactly three live neighbours becomes a live cell, as if by reproduction.
  • 5. Thomas Schelling (1969). Models of Segregation. PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING. "Imagine a line along which blacks and whites have been distributed in equal numbers and random order... Define everybody's 'neighbourhood' as extending four neighbours on either side, and suppose that everyone is content if half his 'neighbours' are the same color as he. If fewer than half are his color, he moves in either direction to the nearest point at which half his eight nearest neighbors are the same color as he."
  • 6. Thomas Schelling (1969). Models of Segregation. PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING. "I have put a dot over the individuals that are dissatisfied... Suppose that the dotted individuals move in turn, starting from the left, if they are still discontent when their turns come: rearrange the plusses and zeroes by moving each dotted one to the nearest point where, inserting itself between two others, at least four of its eight neighbors are of its own color.”
  • 7. Thomas Schelling (1969). Models of Segregation. PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING. "Eight have become newly discontent. We give them their turn and... we end up with six groups of alternating color. All of this is too abstract to be a motion picture of whites and blacks or boys and girls choosing houses on a road... but it is suggestive of some of the dynamics that could be present in individually motivated segregation"
  • 8. Axelrod & Hamilton (1981). The Evolution of Cooperation. PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 9. Axelrod & Hamilton (1981). The Evolution of Cooperation. PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING. "With two individuals destined never to meet again, the only strategy that can be called a solution to the game is to defect always... [But] If an individual can recognize a previous interactant and remember some aspects of the prior outcomes, then the strategic situation becomes an integrated Prisoner's Dilemma with a much richer set of possibilities." "[Axelrod] conducted a computer tournament for the Prisoner's Dilemma... [There was] a game length of 200 moves. The 14 entries and a totally random strategy were paired with each other in a round robin tournament... the result of the tournament was that the highest average score was attained by the simplest of all strategies submitted: TIT FOR TAT. This strategy is simply one of cooperating on the first move and then doing whatever the other player did on the preceding move. Thus TIT FOR TAT is a strategy of cooperation based on reciprocity."
  • 10. ABM became widespread in the 1990s - Disease Dynamics in a Refugee Camp - Modelling the Emergence of Riots - Exploring the Growth of Slums - The Spread of Agriculture during the Neolithic Period Crooks, Malleson et al. (2018). Agent-Based Modelling and Geographical Information Systems. PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 11. Critique - Ontology Livet, Phan & Sanders (2008). Why do we need Ontology for Agent-Based Models. 'the question of the ontological compatibility between the “model world” and the “real world.’ - Causal Explanation Grune-Yanoff (2008). The explanatory potential of artificial societies. '... models do not provide potential causal explanations. Instead... they provide potential functional explanations.' PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 12. PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING. Simple Example: Rabbit Population Growth https://github.com/peterprescott/agent-based-modelling
  • 13. Simple ABM: Create Environment PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 14. Simple ABM: Define Agent PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 15. Simple ABM: Define Agent Behaviour PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 16. Simple ABM: Define a Rabbit PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 17. Simple ABM: Define Rabbit Behaviour (1) PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 18. Simple ABM: Define Rabbit Behaviour (2) PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 19. Simple ABM: Define Rabbit Behaviour (3) PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.
  • 20. Simple ABM: Extend Model… PETER PRESCOTT (2019). A BRIEF INTRODUCTION TO AGENT-BASED MODELLING.