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InteractionsProfile
Samuel Gomes edited this page Dec 2, 2019
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This class adds to the data model of an Interactions Profile some utility methods used to calculate distances.
InteractionsProfile(K_i, K_cp, K_mh, K_pa): void| Name: expected type | Default value | Description |
|---|---|---|
| K_i: float | 0 | The "individual" dimension |
| K_cp: float | 0 | The "competition" dimension |
| K_mh: float | 0 | The "mutual help" dimension |
| K_pa: float | 0 | The "psychic altruistic" dimension |
distanceBetween(profileToTest): floatCalculates the euclidean distance between this and other profile.
| Name: expected type | Default value | Description |
|---|---|---|
| profileToTest: InteractionsProfile | - | The other profile to compare |
sqrDistanceBetween(profileToTest): floatCalculates the squared euclidean distance between this and other profile.
| Name: expected type | Default value | Description |
|---|---|---|
| profileToTest: InteractionsProfile | - | The other profile to compare |
normalizedDistanceBetween(profileToTest): floatCalculates the normalized euclidean distance between this and other profile.
| Name: expected type | Default value | Description |
|---|---|---|
| profileToTest: InteractionsProfile | - | The other profile to compare |
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