[This is preliminary documentation and is subject to change.]
The MetaCognitiveModule..::..MetaCognitiveModuleParameters type exposes the following members.
Properties
Name | Description | |
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DELETION_FREQUENCY |
The frequency (in terms of # of learning steps) in which deletions by density are to be performed
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DISCOUNT |
The match discount factor to be applied at the end of an episode
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FIXED_BL_LEVEL_SELECTION_MEASURE |
The fixed selection measure for the bottom level
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FIXED_RER_LEVEL_SELECTION_MEASURE |
The fixed selection measure for the RER rules
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IsGlobal |
Used to specify whether the particular instance of the parameters class is being used for global or local parameters
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OPERATION_OPTION |
Specifies the type of operation that is being performed by the module (for use in InterpretMetaCognition(LocalEpisodicMemoryTuple))
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OUTCOME_ACTIVATION_OPTION |
Specifies how the activation(s) for the module's outcome should be set (for use in
InterpretMetaCognition(LocalEpisodicMemoryTuple))
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ParameterChange_EventInvoked |
Used to specify that a global parameter change event in in progress
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PERFORM_BL_LEARNING |
Specifies whether or not bottom level learning should be performed
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PERFORM_DELETION_BY_DENSITY |
Specifies whether or not intermittent rule deletion by density should be performed
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PERFORM_LEARNING |
Specifies whether or not learning in general (including extraction, refinement, bottom-level learning, deletion by density, etc.)
should be performed
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PERFORM_REFINEMENT |
Specifies whether or not rule refinement should be performed
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PERFORM_RULE_EXTRACTION |
Specifies whether or not rule extraction should be performed
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PERFORM_TOP_DOWN_LEARNING |
Specifies whether or not top-down learning should be performed
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PERSISTENCE |
The persistence factor for the previous selection
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POSITIVE_MATCH_THRESHOLD |
The threshold for the positive match criterion of the top and bottom level component collections
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SELECTION_TEMPERATURE |
The temperature for stochastic selection
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SELECTION_THRESHOLD |
The threshold for stochastic selection
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