Research Methods and Resources
4.11 Simple Agent-Based Model Design and Development
Before an ABM of climate-induced migration in Burkina Faso could be constructed and the important interactions between agents defined, a basic, representative demographic model of the Burkinabé population was developed. This model included processes of birth, marriage and death in order to capture underlying demographic structures before the introduction of agent-agent interaction, agent-agent-environment interaction and migration decision-making. The model developed by this thesis starts in the year 1970 and is populated with agents that are initialised from individual entries in the EMIUB dataset. As a result, each model agent initialised into the model in 1970 has attributes that reflect those of an EMIUB survey respondent who was alive that year. Rather than use the precise coordinates of each agent’s location at any point in time (a computationally demanding endeavour requiring a large database containing latitude and longitude reference data) the locations of all agents were defined simply on the basis of the EMIUB zone within which they were born. As a result, all agents representing EMIUB surveyed individuals born in the Sahel zone will initialise into the model in a random location within that zone.
Using the five zones into which the EMIUB data divides Burkina Faso permitted agents to be easily located into the correct zone using the same data source used to inform other attributes such as age, gender and marital status. In addition, using a zone level of agent distribution reduced model complexity and allowed clear identification of a threshold beyond which an agent’s movement would be classed as ‘migration’. Rather than defining a distance greater than which an agent’s relocation might be classed as migration when they select one of numerous destination options, the division of Burkina Faso into distinct zones allows a simple definition of migration that is easily observed and quantified within the confines of the output of the model.
The first step in constructing an ABM using AnyLogic was to create and define the active object classes, or agents, of the model. In order to align with the geographical structure of the EMIUB data, defined by five distinct zones within three of the four rainfall zones identified by Henry et al. (2004a), five active object classes were created. These five agent classes represent the population of EMIUB surveyed individuals alive in 1970 and born in each respective zone. The virtual environment constructed within the model contained the five sets of agents and was visually defined using an image of Burkina Faso that displays the five model zones (Figure 4.9).
By placing the agents within a virtual environment it is possible to control such important components as the size of the environment, the type of space that environment comprises (discrete or continuous), the layout of the agents on model start-up and the type of network to which agents can belong.
The model environment selected for the ABM constructed by this thesis was a 2D continuous environment. Use of such an environment permits the current location of an agent to be both set and retrieved, allows agents to be moved with specified speed from one location to another, and allows connections to be established between agents. As well as defining agents and their environment within the model, an important stage in the development of an ABM in AnyLogic is the definition of time. The model time units used by the model were defined as ‘days’ through the use of a calendar to run the model from and to defined start and end points. In early versions of the model it was run for the thirty year period from the 1st January 1970 to the 31st December 1999.
On model startup agents retrieve age, gender, marital status, migration experience and employment attributes stored within connected Excel spreadsheets and populate their respective zones. Each of the attributes retrieved by an agent from the Excel spreadsheets represent real individuals recorded by the EMIUB as alive in 1970. Although the study was conducted in 2000, the retrospective nature of the survey provides temporal data on the surveyed individuals.
For example, a 47 year old married individual interviewed in 2000 may provide attributes for an unmarried modelled agent with a 1970 age of 17. The main motive for modelling agents from a past state is the greater ease of model validation that can be undertaken by direct comparison of observed and modelled migrants. Starting from an initial agent state defined at 1970, it is possible to more accurately recreate past flows using past circumstances.
When the EMIUB survey was conducted in the year 2000 only people over the age of 15 were interviewed. As a result, using a population demographic that used year 2000 data would result in no agents aged 14 and under being present at model startup. This would lead to either a 15 year gap between the youngest initial agents and those ‘born’ into the model, or the need to make up the attributes of a younger generation to fill the void. By using 1970 attributes of surveyed agents, although reducing the number of agents for whom data is available (due to the retrospective nature of the survey), the accuracy with which the agent population is represented is increased. This does however then present the problem that older people are not included in the 1970 population. In order for someone of 60 years of age in 1970 to have been surveyed in 2000 they would have had to be 90 years old. However, the lack of older modelled agents will have been remedied by the time a model run has reached 1999 as a result of the ageing model population. As such the demographic structure of the model population will not affect migrant numbers modelled post-2000 in later model applications.
Following the method of agent initialisation described above, the number of agents initially inhabiting each of the five model zones is limited to the number of people surveyed in 2000 but recorded as living in each zone in 1970. As a result, 661 agents were initialised into Ouagadougou, 893 into Bobo Dioulasso, 898 into Sahel, 1,363 into Centre and 634 into Southwest. Intended as a representative survey, the EMIUB data individuals initialised into the model zones as agents should broadly represent the real demographic structure of those zones.
The EMIUB attributes assigned to individuals update as the model progresses forwards from 1970 in the manner displayed in Figure 4.10. On a predefined increment of time agent variables such as age and marital status, as well as zone level variables such as population, are updated to reflect the change in characteristics that have occurred between time ‘t’ and time ‘t + 1’.
Figure 4.10: Diagrammatic representation of the means by which agent attributes are updated as model time progresses.