Intelligent control with hierarchical stacked neural networks

• US 9,015,093 B1
• Filed: 10/25/2011
• Issued: 04/21/2015
• Est. Priority Date: 10/26/2010
• Status: Active Grant

• Current Assignee: Michael Lamport Commons
• Original Assignee: Michael Lamport Commons
• Inventors: Commons, Michael Lamport
• Primary Examiner(s): Nguyen, John Q
• Assistant Examiner(s): KIM, KYUNG J
• Application Number:
  US13/281,347
• Time in Patent Office: 1,274 Days
• Field of Search: 701/23, 706/26
• US Class Current: 706/26
• CPC Class Codes: B60W 30/00 Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
• CPC Class Codes: F02D 41/1405 Neural network control
• CPC Class Codes: F03D 7/046 with learning or adaptive control, e.g. self-tuning, fuzzy logic or neural network
• CPC Class Codes: G01C 21/3602 Input other than that of destination using image analysis, e.g. detection of road signs, lanes, buildings, real preceding vehicles using a camera
• CPC Class Codes: G05B 2219/25255 Neural network
• CPC Class Codes: G05B 2219/41054 Using neural network techniques
• CPC Class Codes: G06N 3/00 Computing arrangements based on biological models
• CPC Class Codes: G06N 3/02 Neural networks
• CPC Class Codes: G06N 3/04 Architecture, e.g. interconnection topology
• CPC Class Codes: G06N 3/045 Combinations of networks
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 7/046 Implementation by means of a neural network neural networks using fuzzy logic G06N3/043
• CPC Class Codes: Y10S 128/925 Neural network

Abstract

A method of processing information is provided. The method involves receiving a message; processing the message with a trained artificial neural network based processor, having at least one set of outputs which represent information in a non-arbitrary organization of actions based on an architecture of the artificial neural network based processor and the training; representing as a noise vector at least one data pattern in the message which is incompletely represented in the non-arbitrary organization of actions; analyzing the noise vector distinctly from the trained artificial neural network; searching at least one database; and generating an output in dependence on said analyzing and said searching.

Claims

1. At least one processor configured to automatically carry out a sensory-motor task, comprising:

an input configured to receive information;

a hierarchical stacked neural network comprising at least three hierarchically interconnected neural network layers, each neural network layer above a lowest hierarchical level comprising at least a plurality of input neurons receiving a plurality of respective layer inputs from a preceding hierarchical level neural network layer, which influence a plurality of output neurons of the respective neural network layer to produce a plurality of respective layer outputs, each respective neural network layer having a plurality of parameters representing training of the respective neural network layer, wherein the respective layer outputs comprise a non-arbitrary organization of actions, each respective neural network layer being configured to interpret the information according to successive stages of cognitive development, and respectively higher neural network layers being configured to provide feedback to respectively lower neural network layers to adjust the plurality of parameters;

an interface configured to communicate a query for search of at least one external database defined by an output of at least one layer of the hierarchical stacked neural network, and for returning data corresponding to the search to at least one layer of the hierarchical stacked neural network higher than the at least one layer of the hierarchical stacked neural network which defined the query, for processing therein; and

a motor network configured to control the sensory-motor task based on an output from the hierarchical stacked neural network, being dependent on the returned data.

2. The at least one processor of claim 1, wherein the sensory-motor task comprises driving a motor vehicle.

3. The at least one processor of claim 1, wherein the input comprises at least one of a camera and a microphone.

4. The at least one processor of claim 1, wherein the information comprises at least one of a visual information and an audio information.

5. The at least one processor of claim 1, wherein the interface comprises a machine-machine interface configured to communicate with and control a device having an automated controller of a database server.

6. The at least one processor of claim 1, wherein the database comprises a navigational database and the sensory-motor task comprises vehicular travel.

7. The at least one processor of claim 1, wherein the database comprises an unstructured database of documents.

8. A method of automatically performing a sensory-motor task, comprising:

receiving an input comprising sensory information from an environment;

interpreting the sensory information in a hierarchical stacked neural network comprising at least three layers, each layer comprising at least a plurality of input neurons which influence a plurality of output neurons, and being associated with a plurality of weights, each layer producing a non-arbitrary organization of actions representing a level of cognitive development respectively higher than a level of cognitive development represented in inputs to the respective layer, and respectively higher layers providing feedback to respectively lower levels;

searching at least one external database comprising information relevant to at least one of the environment and the sensory-motor task, based on an output of at least one layer of the hierarchical stacked neural network;

receiving a response from the searching of the at least one external database by the hierarchical stacked neural network as an input of at least one layer at a respectively higher layer than the output of the at least one layer that produced the output;

processing the received response by at least the hierarchical stacked neural network to define a sensory-motor effect; and

providing an output comprising a representation of effector signals for controlling the sensory-motor task.

9. The method of claim 8, wherein at least a portion of the effector signals are generated on the basis of a database search.

10. The method of claim 9, wherein the hierarchical stacked neural network communicates with the database through the Internet.

11. The method of claim 8, wherein the sensory-motor task comprises driving a motor vehicle.

12. The method of claim 8, wherein the sensory information comprises a signal generated by at least one of a camera and a microphone.

13. The method of claim 8, wherein the sensory information comprises at least one of a visual information and an audio information.

14. The method of claim 8, wherein the effector signals are produced in dependence on a rule-based module controlled by at least one layer of the hierarchical stacked neural network.

15. The method according to claim 8, wherein the output of at least one layer of the hierarchical stacked neural network for said searching of the at least one database comprises a semantic query, and the received response from the searching of the at least one database comprises at least one web page.

16. A processor configured to carry out a sensory-motor task, comprising:

an input configured to receive environmental information;

a hierarchical stacked neural network comprising at least three layers operating at different levels of cognitive development;

each layer comprising at least one programmable inter-neuron weight and each layer below a highest layer receiving feedback from a respective higher layer, and being configured to interpret abstract information represented in the environmental information and to produce a non-arbitrary organization of actions dependent on the respective level of cognitive development;

a module configured to conduct an external database search controlled by at least the hierarchical stacked neural network representing at least a non-arbitrary organization of actions of a query layer of the hierarchical stacked neural network based on a goal of the sensory-motor task and the environmental information, a response to the external database search being provided as an input to the hierarchical stacked neural network and being processed by at least one layer of the hierarchical stacked neural network above a level of the query layer; and

a module configured to generate control information relating to a manner of carrying out the sensory-motor task based at least on an output of the hierarchical stacked neural network dependent on a result of the module configured to conduct an external database search.

17. The processor of claim 16, wherein the hierarchical stacked neural network communicates with the database through the Internet.

18. The processor of claim 16, wherein the sensory-motor task comprises driving a motor vehicle.

19. The processor of claim 16, wherein a source of the input comprises at least one of a camera and a microphone.

20. The processor of claim 16, wherein the environmental information comprises at least one of a visual information and an audio information.

21. The processor of claim 16, wherein the database comprises a location information database.