The applet requires Java 1.4.1 or higher. It will not run on Windows 95 or Mac OS 8 or 9. Mac users must have OS X 10.2.6 or higher and use a browser that supports Java 1.4. (Safari works, IE does not. Mac OS X comes with Safari. Open Safari and set it as your default web browser under Safari/Preferences/General.) On other operating systems, you may obtain the latest Java plugin from Sun's Java site.
powered by NetLogo
view/download model file: learning_and_horse_races.nlogo
The model explores the evolution over time of the learning process of punters (people who bet on horses). The object of the model is the demonstratation of the usefulness of learning process for punters in order to gain more money than a punter unaware of the horses database wins.
There are a lot of variations to this model.
First of all horses run in the racecourse until one of them crosses the white line (the finish line). Focusing on horses, are given two main possibilities:
- horses compete with random speed without own characteritics;
- horses compete as well with random speed, but set with horses characteristics, such as health, unpredictability, acceleration and progression.
Horses' characteristics are also linked to typology of terrain (grass or mud). The percentage of mud can be externally chosen.
When race starts punters choose an horse to "punt" on. The bet amount can be established using two different possibilities:
- each punter bets the same amount, externally chosen;
- each punter bets a different amount, linked to their characteristics, such as aggressiveness, information and wealth.
Learning process of punters is based on a different grade of awareness, that consist on a different number of races observed. Starting from this level of awarenes each punter calculate the percentage of single horse wins. Thanks to the odds of each horse, every punter can finally estimate the exspexted gain value and "punt" on horse with highest value.
1. Set the equal-speed? switch to TRUE to ignore horses' characteristics, or to FALSE to observe differentiated horses.
2. Set the equal-bet? switch to TRUE to make punters "punt" the same amount, or to FALSE to make them bet considering their characteristics.
3. Set the Show-money? switch to TRUE to disclose punters' "money-label", or to FALSE to hide them.
4. Adjust the following slider parameters:
a. mud-probability
b. injury-probability
c. Starting-money
d. amount-bet
e. Starting-cash
f. learning-" " for each punter
5. Press the SETUP button.
6. Press the START button to begin the simulation
7. Look at the monitors to see:
a. number of single horse wins
b. percentage of single horse wins
c. horse winner in each race
d. winner horses' odds
8. Look at the "Result races" plot to watch the winning horses' historical database over time
9. Look at the "Money available" plot to watch the residual amount of money for each punter
If equal-speed? is set to TRUE it's more difficult for punters to foretell wich will be the winning horse.
If punters have the same learning grade, then their choices will be identical, because of the same number of races observed.
In the momitor named "odds-winner", if an horse wins two close races, is possible to notice its decreasing odds.
The model let to try many combinations. Here there are some parameter to combinate each other:
1. Terrain homogeneous grassy, homogeneous muddy or mixed;
2. Horses with same or different characteristics;
3. Punters with same or different bet amount;
4. High or low injury probability for horses;
5. Different levels of learning process (absent, complete or scaled);
6. Punters with same or different learning grade.
It is possible to extend the model by adding the observe's opportunity to participate as the seventh punter.