Method and apparatus for modeling probability matching human subjects in n-arm bandit tasks
AssigneeHRL Laboratories, LLC
InventorsSuhas E. Chelian, Rajan Bhattacharyya
Life of this patent
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Abstract
Described is a system for modeling probability matching in human subjects. Features related to probability matching are extracted from a set of human subject responses from behavioral tasks. Neural network model instances are trained on the set of features, resulting in a set of trained neural network model instances. A set of model parameters are derived from the set of trained neural network instances, and the set of derived model parameters are used to emulate human performance on novel data.
Claims12
A system for modeling probability matching among human subjects for employee training, the system comprising:
- one or more processors and a non-transitory computer-readable medium having executable instructions encoded thereon such that when executed, the one or more processors perform operations of:
- extracting a set of features related to probability matching from a set of data comprising human subject responses from behavioral tasks related to a skill;
- training neural network model instances on the set of features, resulting in a set of trained neural network model instances;
- deriving a set of model parameters from the set of trained neural network instances;
- generating a model of human behavior using the set of derived model parameters;
- applying the model of human behavior to a set of new data comprising employee responses;
- automatically selecting one or more employees for training in the skill.
A computer-implemented method for modeling probability matching among human subjects for employee training, comprising:
- an act of causing one or more processors to execute instructions stored on a non-transitory memory such that upon execution, the one or more processors perform operations of:
- extracting a set of features related to probability matching from a set of data comprising human subject responses from behavioral tasks related to a skill;
- training neural network model instances on the set of features, resulting in a set of trained neural network model instances;
- deriving a set of model parameters from the set of trained neural network instances;
- generating a model of human behavior using the set of derived model parameters;
- applying the model of human behavior to a set of new data comprising employee responses;
- automatically selecting one or more employees for training in the skill.
A computer program product for modeling probability matching among human subjects for employee training, the computer program product comprising:
- computer-readable instructions stored on a non-transitory computer-readable medium that are executable by a computer having one or more processors for causing the processor to perform operations of:
- extracting a set of features related to probability matching from a set of data comprising human subject responses from behavioral tasks related to a skill;
- training neural network model instances on the set of features, resulting in a set of trained neural network model instances;
- deriving a set of model parameters from the set of trained neural network instances;
- generating a model of human behavior using the set of derived model parameters;
- applying the model of human behavior to a set of new data comprising employee responses;
- automatically selecting one or more employees for training in the skill.
Dependencies are inferred from the claim text.