ExplorationPreferencesEstAlg

ExplorationPreferencesEstAlg is an algorithm that explores different players' possible preferences and picks the best one. It acts in a similar way to PureRandomSearchConfigsGenAlg, in the sense that it tests several profiles and picks the one found closer to the real preference of a learner.

Constructor and Members

Constructor

ExplorationPreferencesEstAlg(
        player_model_bridge: PlayerModelBridge,
        interactions_profile_template: InteractionsProfile,
        quality_eval_alg: QualityEvalAlg,
        num_tested_player_profiles: int): void

Members

Name: expected type	Default value	Description
__interactions_profile_template: InteractionsProfile	-	A template for creating new profiles. The template acts as a facilitator to not only the number of interaction dimensions to be considered, but also their designations.
__quality_eval_alg: QualityEvalAlg	-	The regression algorithm to be used in the adaptation iterations.
__num_tested_player_profiles: int	100	The number of tested profiles when determining each learner's preference.

Functions

Overrides updateEstimates() (see PreferencesEstAlg).