These models and simulations have been tagged “Real Estate”.
Assignment 3 – Complex Systems
Salvaggio - 43668070
conceptualizes the effects on a real-estate market-model utilizing agent based
modelling. This model utilizes basic economic principles of supply and
The model bases
itself on two Agents - one being ‘Customers’ of the real estate market model,
whilst the other being the Real estate itself, coined 'Houses'.
The Agent population, ‘Consumers’
specifies the total amount of people whom can potentially become buyers within
the market. This is limited to 30 for conceptual purposes. The Agent ‘Consumer’
exists in two states, either being an ‘Active Customer’ (Active) or an
‘Inactive Customer’ (Inactive). The transition from Inactive to
Active occurs upon the basis that the ‘Budget’ of the Consumer meets the
desired price of the marketplace, this is specified through the variable
‘Budget’ defining the probability that this transition will occur – this is
adjustable by the user indicating a highly resistive or by accepting the market.
‘Budget’s probability in a real life scenario would be based upon numerous
factors however conceptually utilizing the slider can present many of these
transitioning into an active state an ‘Active consumer’ will attempt to find
the closest ‘For sale household’, this is represented and carried out through
the ‘Enter’ action. Upon finding a household the consumer and house
will both return to their respected inactive state thus repeating the process.
Demand – ‘Count
of active customers – demand’ is then calculated by a count of Consumers
transitioned and currently in the Active state. A high demand would be
indicative through a high ‘Budget’ responsiveness whilst a low demand would be
indicative of a low ‘Budget’ responsiveness. The increase in Price and hence
supply of household thus reduces demand and vise versa.
population, ‘Houses’ specifies the total amount of households that can potentially
become for sale within the market. This is limited to 112 for conceptual
purposes. The Agent ‘House’ exists in two states, either being ‘For Sale’
(Active) or ‘Not for Sale’ (Inactive). The transition from Inactive
to Active occurs upon the basis that the ‘Motivation to Sell’ of the House is
satisfied, this satisfaction is specified by a set probability that this
transition will occur – this is adjustable by the user indicating a highly
responsive or restricted house market. ‘Motivation to sell’ probability in a
real life scenario would be based upon numerous factors however conceptually
utilizing the slider can present many of these various situations.
into an active state a ‘For Sale’ house will wait for an ‘Active Customer’ ‘this
is represented and carried out through the ‘Search’ action. Upon completion of
the action both states become inactive and the process continues.
Supply – ‘Count
of houses for sale –supply’ is then calculated by a count of Houses ‘For Sale’
that are currently in the active state. Ultimately a high Motivation to sell
would sharply increase supply, whilst a low motivation would have the adverse
Movement speed –
describes the base movement rate of Consumers. This variable describes the
transition into the ‘Inactive’ state of a consumer, ultimately when a household
is found and purchased. Movement speed affects both demand and supply in the
sense that the transitioning of stages is quickened and more responsive.
(Indicated by a more rigid demand and supply curve).
In economics Price is a linear function
(straight line) of the proportion of houses for sale (positive slope), and also
a linear function of the proportion of buyers (negative slope).Therefore , the
variable ‘Market Price’ is calculated by 10 * the portion of ‘House’ in the
active state (which is the supply) over the portion of ‘Consumers’ in the
active state (which is the demand) Ultimately this presents the economic
principles that as Supply is directly related to Price and demand
is inversely related to Price.
Each simulation (with
the same settings) will present a different and unique simulation. I have set a
Random Boolean to the active component that randomizes the amount of Customers
or houses that begin in their active state. The probability is only 0.008 but
is useful in describing the effects on the market from various position’s and
seeing unique models.
- Your First ABM/Part II
For example if supply is higher than demand or if demand is
not that high to begin with than the price will drop accordingly and vice
versa. If there are less willing buyers than unwilling buyers then the demand
will go down. The supply and demand relatable to each other.
According to the simulation if price is fairly low supply
and demand will steadily increase however at a certain point it starts to sky
rocket and supply and demand gradually declines.