Human-machine interactions
View Patent ↗Digital technology utilizing a cognitive model based on human naturalistic decision-making processes, including pattern recognition and episodic memory, can reduce the dependency of human-machine interactions on the abilities of a human user and can enable a machine to more closely emulate human-like responses. Such a cognitive model can enable digital technology to use cognitive capacities fundamental to human-like communication and cooperation to interact with humans.
1. An apparatus for enhancing human task performance, the apparatus comprising:
a first input for obtaining a first set of data descriptive of a current environment;
a first modeler for creating a first representation of the current environment based on the first set of data;
a second input for obtaining a second set of data descriptive of at least one action of a user;
a second modeler for creating a second representation of the current environment including the at least one action of the user based on the second set of data;
a detector for detecting at least one difference between the first representation and the second representation; and
an interface for providing the at least one difference to the user.
2. The apparatus of claim 1 , wherein said first modeler includes:
a library for storing a set of information representative or environments previously encountered by the apparatus;
an episodic memory unit for providing a history of previously performed actions taken in environments previously encountered by the apparatus, said episodic memory unit using the set of information from the library to create the history;
a pattern recognizer for recognizing a pattern between the current environment and the history; and
a semantic unit for receiving the first set of data and preparing the first set of data for pattern recognition by said pattern recognizer.
3. The apparatus of claim 2 , wherein said semantic unit includes a network of associations.
4. The apparatus of claim 3 , wherein the network of associations is a network of associations between a set of concepts.
5. The apparatus of claim 3 wherein the network of associations is a network of associations between a set of cues.
6. The apparatus of claim 1 wherein said second modeler includes:
a library for storing a set of information representative of environments previously encountered by the apparatus;
a pattern recognizer for recognizing a pattern between the second set of data and the second set of information; and
a semantic unit for receiving the second set of data and preparing the second set of data for pattern recognition by said pattern recognizer.
7. The apparatus of claim 6 , wherein said semantic unit includes a network of associations.
8. The apparatus of claim 7 , wherein the network of associations is a network of associations between a set of concepts.
9. The apparatus of claim 7 wherein the network of associations is a network of associations between a set of cues.
10. The apparatus of claim 1 wherein said detector includes a comparator for comparing the first representation and the second representation.
11. A method, practiced on an electronic device, for enhancing human task performance, the method comprising:
obtaining a first set of data descriptive of a current environment;
creating a first representation of the current environment based on the first set of data;
obtaining a second set of data descriptive of at least one action of a user;
creating a second representation of the current environment including the at least one action of the user based on the second set of data;
detecting at least one difference between the first representation and the second representation; and
providing the at least one difference to the user.
12. The method of claim 11 , wherein said first creating step includes:
accessing a set of information representative of environments previously encountered;
creating, based on the set of information, a history of previously performed actions taken in environments previously encountered;
preparing the first set of data for pattern recognition; and
recognizing a pattern between the first set of data and the history.
13. The method of claim 12 , wherein said recognizing step includes developing a network of associations.
14. The method of claim 13 , wherein said developing step includes developing a network of associations between a set of concepts.
15. The method of claim 13 wherein said developing step includes developing a network of associations between a set of cues.
16. The method of claim 11 wherein said second creating step includes:
storing a set of information representative of environments previously encountered by the apparatus;
preparing the second set of data for pattern recognition; and
recognizing a pattern between the second set of data and the set of information.
17. The method of claim 16 , wherein said recognizing step includes developing a network of associations.
18. The method of claim 17 , wherein said developing step includes developing a network of associations between a set of concepts.
19. The method of claim 17 wherein said developing step includes developing a network of associations between a set of cues.
20. The method of claim 11 wherein said detecting step includes comparing the first representation and the second representation.