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ExploitationPreferencesEstAlg
Samuel Gomes edited this page Jul 4, 2024
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ExploitationPreferencesEstAlg is an estimation algorithm that values exploitation of the players' current state. When used in conjunction with a purely greedy grouping approach, it gets stuck in the first local maximum.
+ ExploitationPreferencesEstAlg(
playerModelBridge: PlayerModelBridge,
interactionsProfileTemplate: InteractionsProfile,
qualityEvalAlg: QualityEvalAlg,
qualityWeights: PlayerCharacteristics = {ability = 0.5, engagement = 0.5): void| Name: expected type | Default value | Description |
|---|---|---|
| playerModelBridge: PlayerModelBridge | - | The connector for the player data storage. |
| interactionsProfileTemplate: InteractionsProfile | - | A template for creating new profiles, informing the number and name of interaction dimensions to be considered. |
| qualityEvalAlg: QualityEvalAlg | - | The algorithm used to predict the quality of a profile for a player. |
| qualityWeights: PlayerCharacteristics | {ability= 0.5, engagement= 0.5} | The importance given to each player characteristic when computing the quality of a configuration. |
+ updateEstimates(): voidUpdates the personality estimates of all players, directly accessing their models.
- calcQuality(state: PlayerState): decimalComputes the quality of a player state, between 0 and 1. A higher value means better quality.
Adaptation
Group Configuration Generation
- ConfigsGenAlg
- RandomConfigsGenAlg
- PureRandomSearchConfigsGenAlg
- EvolutionaryConfigsGenAlg
- ODPIPConfigsGenAlg (exact)
- CLinkConfigsGenAlg (legacy)
Preferences Estimation
Quality Evaluation Algorithms
- QualityEvalAlg
- Group-Based Quality Evaluation:
- Regression-Based Quality Evaluation:
- Tabular Quality Evaluation:
Auxiliary Structures
- InteractionsProfile
- PlayerCharacteristics
- PlayerState
- Personality (Inherent Preference):
- PlayerStatesDataFrame
Model Bridges
Player Data Trim