ConfigsGenAlg
ConfigsGenAlg is an abstract base class for the group organization algorithms. These algorithms are usually called coalition structure generation algorithms. GIMME implements a few of them, such as a random generation, one which does not save any information between iterations, a genetic driven approach, etc...
ConfigsGenAlg(numberOfConfigChoices, minNumberOfPlayersPerGroup, maxNumberOfPlayersPerGroup, preferredNumberOfPlayersPerGroup, fitnessWeights, regAlg)| Name: expected type | Default value | Description |
|---|---|---|
| playerModelBridge: PlayerModelBridge | - | The connector for the players data model |
| regAlg: RegressionAlg | - | The regression algorithm used to predict new states from the existing ones |
| qualityWeights: PlayerCharacteristics | PlayerCharacteristics(ability=0.5, engagement=0.5) | Weights to consider when calculating the quality of predicted group states |
| numberOfConfigChoices: int | 100 | The connector for the tasks data model |
| minNumberOfPlayersPerGroup: int | 2 | The minimum group size to consider |
| maxNumberOfPlayersPerGroup: int | 5 | The maximum group size to consider |
| preferredNumberOfPlayersPerGroup: int | None | A preferred group size to consider. When filled, the configurations will follow a fixed group size (with the few smaller groups containing the remaining players) |
| configSizeFreqs: int[] | - | The number of times each configuration size was generated (for statistic purposes) | | groupSizeFreqs: int[] | - | The number of times each group size was generated (for statistic purposes) |
reset(): voidAbstract method used to reset the configuration algorithm if data is stored between iterations. Nothing is done otherwise.
organize(): int[][]Actually performs the group organization and returns a group configuration (or coalition structure).
updateMetrics( generatedConfig: int[][] ) : voidUpdates groupSizeFreqs and configSizeFreqs.
| Name: expected type | Default value | Description |
|---|---|---|
| generatedConfig: int[][] | - | The generated group organization |
configsGen = GIMMEConfigsGen(numberOfConfigChoices=50, preferredNumberOfPlayersPerGroup = 5, PlayerCharacteristics(ability=0.9, engagement=0.1))
configsGen.organize(playerModelBridge)