In the years 2000 - 2002 when I started vsoc the following results where documented.
| first trends | First trends for optimal values of mutation rate, steps per match and selection interval |
| Optimal feed forward net (A) | The test uses multiple feed forward nets. They differ in the number of layers and in the numbers of connections between this layers. The number of connections is defined by the probabillyity of connections between two arbitrary nodes of this layers. |
| Optimal Kick Out Factor (KOF) | Watching previous simulations showed the effect, that hitting the ball out of the field was a common task although it is not advatntageous for soccer playing clients. This behaviour was forced by the fact that hitting the ball increases the fittnes of players. Specially if the ball lays near the out line players start to increase their fittness by hitting the ball out again and again. |
| Optimal mutation rate | For these tests feed forward ANNs where used. They where all initialized with random weights at the beginning of each run. One population consists of 21 individuals. From these individuals 6 are choosen to participate at a match. 3 in the right and tree in the left team. They play a match of 200 steps. After the match the following parameters are collected for each player to generate a fitness valule. |
| Optimal Selection Interval | The goal of this test was to determine the optimal selection interval for test runs. This means how many matches should be played before a new generation of players should be generated. Of cours longer selection intervals result in better performance because the diffrent players are oftener tested. But long selection intervalls extend the development time and should be avoided if possible. The question is to find the shortest selection interval that still leads to reasonable results. |
| Optimal Steps per Match | The goal of this test was to determine the optimal steps per for test runs. That means how many steps should should a match at least have to determine reasonable results. A small number of steps per match would increase the performance but the results could lead in wrong directions where bigger numbers of steps per match decrease the performance but you may trust the results. The question is to find the smallest number of steps per match that still leads to reasonable results. |