Self-assembling learning system and apparatus
A self-assembling learning system and apparatus determines self-assembling actions that are expected to reduce uncertainties that are embodied as probabilities and then updates the probabilities in accordance with information that results from the performing of the self-assembling actions. The updated probabilities inform the determination of subsequent self-assembling actions. Neural networks, simulations of multiple potential self-assembling actions, and expected values of information may be applied in determining the self-assembling actions that are to be performed. Sensors may be applied to receive information that inform the updating of probabilities, and the self-assembling apparatus may be a robotic device. Self-assembling actions may comprise modifications to relationships between elements of a computer-implemented system.
1. A computer-implemented method comprising:
determining automatically a first self-assembling action, wherein the first self-assembling action comprises modifying a relationship between two elements of a computer-implemented system, wherein the first self-assembling action is expected to result in a reduction of an uncertainty that is embodied by one or more probabilities;
performing automatically the first self-assembling action;
updating automatically the one or more probabilities based upon an assessment of information that results from the performing of the first self-assembling action;
determining automatically a second self-assembling action, wherein the second self-assembling action comprises modifying a relationship between two elements of the computer-implemented system, wherein the determining of the second self-assembling action is in accordance with the updated one or more probabilities; and
performing automatically the second self-assembling action.
2. The method of claim 1 , further comprising:
determining automatically the first self-assembling action, wherein the first self-assembling action is determined by application of a computer-implemented neural network.
3. The method of claim 1 , further comprising:
determining automatically the second self-assembling action, wherein the second self-assembling action is determined by application of a computer-implemented neural network.
4. The method of claim 1 , further comprising:
updating automatically the one or more probabilities based upon the assessment of the information that results from the first self-assembling action, wherein the assessment of the information comprises performing an inference from user behavioral information associated with use of the computer-implemented system.
5. The method of claim 1 , further comprising:
determining automatically the second self-assembling action in accordance with the updated one or more probabilities and an expected value of information.
6. The method of claim 5 , further comprising:
determining automatically the second self-assembling action in accordance with the updated one or more probabilities, the expected value of information, and an expected cost.
7. A system comprising one or more processor-based physical devices configured to:
determine a first self-assembling action, wherein the first self-assembling action comprises modifying a relationship between two elements of the one or more processor-based devices, wherein the first self-assembling action is expected to result in a reduction of an uncertainty that is embodied by one or more probabilities;
perform the first self-assembling action;
update the one or more probabilities based upon an assessment of information that results from the performing of the first self-assembling action;
determine automatically a second self-assembling action, wherein the second self-assembling action comprises modifying a relationship between two elements of the one or more processor-based devices, wherein the second self-assembling action is determined in accordance with the updated one or more probabilities; and
perform automatically the second self-assembling action.
8. The system of claim 7 , further comprising the one or more processor-based devices configured to:
determine the first self-assembling action, wherein the first self-assembling action is determined by application of a computer-implemented neural network.
9. The system of claim 8 , further comprising the one or more processor-based devices configured to:
determine the second self-assembling action, wherein the second self-assembling action is determined by application of a computer-implemented neural network.
10. The system of claim 7 , further comprising the one or more processor-based devices configured to:
determine the first self-assembling action, wherein the first self-assembling action is determined by simulating a plurality of self-assembling actions and an expected associated result of each of the plurality of self-assembling actions.
11. The system of claim 7 , further comprising the one or more processor-based devices configured to:
update the one or more probabilities based upon the assessment of the information that results from the performing of the first self-assembling action, wherein the assessment of the result comprises performing an inference from user behavioral information associated with use of the one or more processor-based devices.
12. The system of claim 7 , further comprising the one or more processor-based devices configured to:
determine the second self-assembling action in accordance with the updated one or more probabilities and an expected value of information.
13. The system of claim 12 , further comprising the one or more processor-based devices configured to:
determine the second self-assembling action in accordance with the updated one or more probabilities, the expected value of information, and an expected cost.
14. An apparatus comprising a robotic device, the apparatus further comprising:
one or more sensors;
one or more processors configured to:
determine a first self-assembling action, wherein the first self-assembling action comprises modifying a relationship between two elements of the apparatus, wherein the first self-assembling action is expected to result in a reduction of an uncertainty that is embodied by one or more probabilities;
perform the first self-assembling action;
update the one or more probabilities by applying the one or more sensors to gather information that results from the performing of the first self-assembling action;
determine automatically a second self-assembling action, wherein the second self-assembling action comprises modifying a relationship between two elements of the apparatus, wherein the second self-assembling action is determined in accordance with the updated one or more probabilities; and
perform automatically the second self-assembling action.
15. The apparatus of claim 14 , further comprising the one or more processors configured to:
determine the first self-assembling action, wherein the first self-assembling action is determined by application of a computer-implemented neural network.
16. The apparatus of claim 14 , further comprising the one or more processors configured to:
determine the first self-assembling action, wherein first self-assembling action is determined by simulating a plurality of self-assembling actions and an expected associated result of each of the plurality of self-assembling actions.
17. The apparatus of claim 14 , further comprising the one or more processors configured to:
determine the second self-assembling action, wherein the second self-assembling action is determined in accordance with the updated one or more probabilities and a value of information.