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CLASS 706, DATA PROCESSING - ARTIFICIAL INTELLIGENCE

1	FUZZY LOGIC HARDWARE:

This subclass is indented under the class definition. Subject matter comprising a specific circuit arrangement for performing approximate reasoning where truth values and quantifiers are represented by possibility distributions.

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52,	for knowledge processing system using fuzzy logic and having no fuzzy logic hardware.
900,	for cross-reference art collection of a data processing system having fuzzy logic data processing.

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326,	Electronic Digital Logic Circuitry, subclasses 59+ for logic circuits responsive to three or more logic signal states, or produces three or more different output logic signal states.

2	. Fuzzy neural network:

This subclass is indented under subclass 1. Subject matter comprising interconnected processors that perform the approximate reasoning.

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15+,	for neural networks having no fuzzy logic hardware.

3	. Analog fuzzy computer (e.g., controller):

This subclass is indented under subclass 1. Subject matter wherein the circuit arrangement comprises electrical components that perform arithmetic operations upon electrical signals, which are continuously varying representations of physical quantities or which are some function of quantities.

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700,	Data Processing: Generic Control Systems or Specific Applications, subclass 50 for adaptive control using fuzzy logic.
701,	Data Processing: Vehicles, Navigation, and Relative Location, subclass 27 for automatic route guidance using fuzzy logic.
708,	Electrical Computers: Arithmetic Processing and Calculating, subclasses 800 through 854for electric analog computers.

4	. Digital fuzzy computer (e.g., controller):

This subclass is indented under subclass 1. Subject matter wherein the circuit arrangement comprises electrical components that perform calculation upon discrete electrical signals representing a value normally described by numerical digits.

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708,	Electrical Computers: Arithmetic Processing and Calculating, subclasses 100 through 714for digital calculating computers.

5	. Having function generator:

This subclass is indented under subclass 1. Subject matter wherein the circuit arrangement contains an electrical device capable of producing one or more functions for fuzzy sets.

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7,	for fuzzy logic hardware having a function calculator.

6	.. By neural network:

This subclass is indented under subclass 5. Subject matter wherein the function generator is controlled by a parallel distributed processing processor constructed in hardware or simulated in software.

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15+,	for neural networks having no fuzzy logic hardware.

7	. Having a function calculator:

This subclass is indented under subclass 1. Subject matter wherein the circuit arrangement contains at least a function calculator.

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5+,	for fuzzy logic hardware having a function generator.

8	. Fuzzy inference processing:

	This subclass is indented under subclass 1. Subject matter wherein a conclusion is deduced from a set of rules based on the approximate reasoning.

9	. Defuzzification processing:

	This subclass is indented under subclass 1. Subject matter wherein the circuit arrangement produces a crisp value for a conclusion.

10	PLURAL PROCESSING SYSTEMS:

This subclass is indented under the class definition. Subject matter comprising (1) computers that emulate intelligence connected in parallel or distributed arrangement, or (2) a compound system having as least one significant artificial intelligence system.

(1) Note. This subclass includes (1) distributed intelligent agent architectures and cooperative distributed problem solving systems, (2) plural reasoning methods, i.e., intelligent hybrid processing systems, and (3) multi-tasking intelligent processing systems.

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15+,	for neural network having no fuzzy logic hardware.

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712,	Electrical Computers and Digital Processing Systems: Processing Architectures and Instruction Processing (e.g., Processors), subclasses 1 through 43for processing architecture.

11	HAVING PARTICULAR USER INTERFACE:

This subclass is indented under the class definition. Subject matter wherein presentation of data to a computer operator of a system contains components that enable interaction by (1) nonverbal representations or symbols or (2) statements in standard English syntax

(1) Note. This subclass includes intelligent processing systems having a hypertext/hypermedia component, a s:graphical user interface component, a natural language component, or a speech interface component.

(2) Note. This subclass includes interface agent systems, personal assistant systems, and intelligent help systems.

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61,	for modification of knowledge processing system using a tool.

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345,	Computer Graphics Processing and Selective Visual Display Systems, subclasses 418 through 475for computer graphics processing.
715,	Data Processing: Presentation Processing of Document, Operator Interface Processing, and Screen Saver Display Processing, subclasses 700 through 866for a computer operator interface.

12	MACHINE LEARNING:

This subclass is indented under the class definition. Subject matter wherein a system has the capability to automatically add to its current integrated collection of facts and relationships.

(1) Note. This subclass includes induction, deduction, applications involving learning (i.e., data mining and knowledge discovery) and statistical learning techniques.

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14,	for adaptive complex information processing system.
16+,	for neural network learning task.
25,	for neural network learning method

13	. Genetic algorithm and genetic programming system:

This subclass is indented under subclass 12. Subject matter wherein a system uses a sequence of steps that (1) starts with a group of solutions to a problem, (2) represents each solution as a coded data string, (3) divides and splices a coded data string to create new solutions, and (4) determines fitness of the new solutions.

(1) Note. This subclass includes evolutionary programming (i.e., learn-acquire knowledge, adapt-adjust).

14	ADAPTIVE SYSTEM:

This subclass is indented under the class definition. Subject matter wherein (1) a system continually adjusts its own set of rules (e.g., learns by example) or (2) a system that evolves in any way into a system which continually adjusts its own set of rules.

(1) Note. This subclass includes tuning membership functions and neural networks that continue to learn after they have been trained (i.e., relearning).

15	NEURAL NETWORK:

This subclass is indented under the class definition. Subject matter including a system which comprises a parallel process performed by a distributed architecture that learns to recognize and classify input data and is (1) constructed in hardware, (2) emulated in software, or (3) a combination of hardware construction and emulation software.

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2,	for fuzzy neural network

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700,	Data Processing: Generic Control Systems or Specific Applications, subclass 48 for a neural network used in a control system.
704,	Data Processing: Speech Signal Processing, Linguistics, Language Translation, and Audio Compression/Decompression, subclasses 202+ for neural network in speech signal processing storage, subclasses 232+ for neural network in speech signal processing recognition and subclasses 259+ for neural network in speech signal processing synthesis.

16	. Learning task:

This subclass is indented under subclass 15. Subject matter wherein the system is trained to accomplish a specific application.

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12,	for machine learning.

17	.. Approximation:

This subclass is indented under subclass 16. Subject matter wherein the system estimates a solution to a function from input data.

(1) Note. This subclass includes transformation and function approximation.

18	.. Association:

This subclass is indented under subclass 16. Subject matter wherein the system learns to identify stored patterns similar to input patterns.

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20,	for neural network having learning task classification or recognition.

19	.. Constraint optimization problem solving:

	This subclass is indented under subclass 16. Subject matter wherein the system finds a best solution from specific input data.

20	.. Classification or recognition:

This subclass is indented under subclass 16. Subject matter wherein the system learns to categorize or identify input data.

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18,	for neural network having learning task association.

21	.. Prediction:

	This subclass is indented under subclass 16. Subject matter wherein the system learns to forecast future patterns from input patterns.

22	.. Signal processing (e.g., filter):

	This subclass is indented under subclass 16. Subject matter wherein the system intentionally changes characteristics of a conveyer of information.

23	.. Control:

This subclass is indented under subclass 16. Subject matter wherein the system models, monitors, or regulates a physical system.

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903+,

for cross reference art collection of an artificial intelligence system having details of control.

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700,	Data Processing: Generic Control Systems or Specific Applications, subclasses 1 through 89for generic data processing control systems, per se.

24	.. Beamforming(e.g., target location, radar):

This subclass is indented under subclass 16. Subject matter wherein the system decides correct direction for a collection of parallel rays.

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250,	Radiant Energy, various subclasses for methods and apparatus involving radiant energy.
342,	Communications: Directive Radio Wave Systems and Devices (e.g. Radar, Radio Navigation), various subclasses for transmission or reception of radio wave energy for obtaining or utilizing information.
359,	Optical: Systems and Elements, various subclasses for optical elements and optical systems not elsewhere classified.

25	. Learning method:

This subclass is indented under subclass 15. Subject matter wherein the system acquires its internal set of rules.

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12,	for machine learning.

26	. Structure:

This subclass is indented under subclass 15. Subject matter wherein the system contains construction details of processors or their interconnections.

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326,	Electronic Digital Logic Circuitry, subclasses 36+ for threshold (e.g., majority) digital logic which may be utilizable for neural networks.

27	.. Architecture:

This subclass is indented under subclass 26. Subject matter wherein the structure (1) are organized for a specific network topology or (2) use neural processors to perform specific transform functions.

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712,	Electrical Computers and Digital Processing Systems: Processing Architectures and Instruction Processing (e.g., Processors), subclasses 1 through 43for processing architecture, in general.

28	... Modular:

	This subclass is indented under subclass 27. Subject matter wherein the architecture comprises a plurality of identical modules of neural networks.

29	... Lattice:

	This subclass is indented under subclass 27. Subject matter wherein the architecture comprises a plurality of locally interconnected neuron processors.

30	... Recurrent:

	This subclass is indented under subclass 27. Subject matter wherein the architecture comprises feedback interconnections.

31	... Multilayer feedforward:

	This subclass is indented under subclass 27. Subject matter wherein the architecture comprises two or more groups of neural processors, where at least one group of neural processors bypasses a group of neural processors.

32	... Single-layer:

	This subclass is indented under subclass 27. Subject matter wherein the architecture comprises one group of processors.

33	.. Semiconductor neural network:

This subclass is indented under subclass 26. Subject matter wherein the structure contains a solid or liquid electronic conductor in which an electrical charge carrier concentration increases with increasing temperature over a temperature range.

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257,	Active Solid-State Devices (e.g., Transistors, Solid-State Diodes), various subclasses for semiconductor devices, per se.

34	.. Hybrid network (i.e., analog and digital):

	This subclass is indented under subclass 26. Subject matter wherein the structure contains analog and digital components.

35	... Using pulse modulation:

Subject matter undersubclass 34 wherein the hybrid network uses an electrical voltage having a definite rise and decay that varies in amplitude, frequency or phase.

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332,	Modulators, subclasses 106+ for pulse modulators, per se.

36	... Having multiplying digital-to-analog converter:

This subclass is indented under subclass 34. Subject matter wherein the hybrid network contains a device that (1) outputs a product of a magnitude represented by two or more input signals and (2) changes pulse(bit) signals to continuous signals.

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341,	Coded Data Generation or Conversion, subclasses 126+ for analog to or from digital conversion, per se.

37	... Having digital weight:

	This subclass is indented under subclass 34. Subject matter wherein the hybrid network comprises interconnections of bits (maintained in a binary memory) that represent a numerical value as a function of bit position code word.

38	.. Analog neural network:

	This subclass is indented under subclass 26. Subject matter wherein the structure comprises representations of numerical quantities by means of physical variables.

39	... Modifiable weight:

	This subclass is indented under subclass 38. Subject matter wherein the analog neural network comprises programmable or adjustable interconnections.

40	.. Radiant energy neural network:

This subclass is indented under subclass 26. Subject matter wherein the structure contains at least a source or detector of radiant wave energy.

(1) Note. This subclass includes optical neural networks.

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359,	Optical: Systems and Elements, subclasses 107+ for optical computing, per se.
382,	Image Analysis, various subclasses for subject matter wherein an image is detected and significant analysis of an image is performed.

41	.. Digital neural network:

	This subclass is indented under subclass 26. Subject matter wherein the structure contains a processing component that can assume only two values.

42	... Parallel connection:

	This subclass is indented under subclass 41. Subject matter comprising an interface in which all bits of data in a given byte are transferred simultaneously, using separate data lines for each bit.

43	... Digital neuron processor:

	This subclass is indented under subclass 41. Subject matter wherein a node of the system comprises logic circuitry that assumes binary values.

44	. Neural simulation environment:

This subclass is indented under subclass 15. Subject matter comprising an apparatus (or method) for developing substitution or testing of actual operational conditions of the system using a general purpose digital computer.

(1) Note. This subclass includes neural network shells and tools.

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60,	for knowledge processing tools.

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703,	Data Processing: Structural Design, Modeling, Simulation, and Emulation, appropriate subclasses.
717,	Data Processing: Software Development, Installation, and Management, subclasses 100 through 167for software program development tools.

45	KNOWLEDGE PROCESSING SYSTEM:

This subclass is indented under the class definition. Subject matter wherein a system comprises specific domain data that (1) is integrated as a collection of facts and relationships (i.e., knowledge representation) and (2) applies a reasoning technique.

(1) Note. This subclass and subclasses indented hereunder provide for details of (1) expert systems or (2) operation of expert systems (either stand alone expert systems or expert systems interacting with other systems).

(2) Note. This subclass and subclasses indented hereunder provide for creation and maintenance of expert systems.

(3) Note. This subclass array accepts combinations of an art class device, or art class method, with artificial intelligence techniques not elsewhere provided for in USPC. This can include mechanical systems, electromagnetic systems, acoustic systems, thermal systems, photonic systems, chemical systems, biological systems, nanomachines and quantum mechanical systems where data or signals are processed according to artificial intelligence methods. A searcher should also consider the relevant art classes and at least the following data processing classes: 700, Data Processing: Generic Control Systems or Specific Applications; 701, Data Processing: Vehicles, Navigation, and Relative Location; 702, Data Processing: Measuring, Calibrating, Or Testing; 703, Data Processing: Structural Design, Modeling, Simulation, and Emulation.

(4) Note. This class can accept combinations of data processing arts with artificial intelligence techniques not elsewhere provided for in USPC. Data processing art in combination with AI can include internet systems, intranet systems, client-server systems, database systems, computer interface systems, multi agent collaboration systems (e.g., societies of agents, groupware), groupware per se, distributed intelligent systems, multi agent systems distributed intelligences, blackboard collaborative systems, social networking methods, hacker detection (e.g., spam detection, data mining, data farming) and artificially intelligent action systems (e.g., web page ranking systems, Eigentrust systems). When mandatory classification is in multiple classes, the ORIGINAL classification may be in a class other than where the application was assigned and examined. A searcher should consider at least the relevant related data processing classes on a case by case basis such as: 700, Data Processing: Generic Control Systems or Specific Applications; 704, Data Processing: Speech Signal Processing, Linguistics, Language Translation, and Audio Compression/Decompression; 705, Data Processing: Financial, Business Practice, Management, or Cost/Price Determination; 707, Data Processing: Database, Data Mining, and File Management or Data Structures; 709, Electrical Computers and Digital Processing Systems: Multicomputer Data Transferring; 710, Electrical Computers and Digital Data Processing Systems: Input/Output; 712, Electrical Computers and Digital Processing Systems: Processing Architectures And Instruction Processing (e.g., Processors); 713, Electrical Computers and Digital Processing Systems: Support; 714, Error Detection/Correction and Fault Detection/Recovery; 715, Data Processing: Presentation Processing of Document, Operator Interface Processing, and Screen Saver Display Processing; 716, Data Processing: Design and Analysis of Circuit or Semiconductor Mask; 717, Data Processing: Software Development, Installation, and Management; 718, Electrical Computers and Digital Processing Systems: Virtual Machine Task or Process Management or Task Management/Control; 719, Electrical Computers and Digital Processing Systems: Interprogram Communication or Interprocess Communication (IPC); 726, Information Security.

(5) Note. This class can accept combinations of data processing arts with artificial intelligence techniques not elsewhere provided for in USPC. Data processing art in combination with AI can include Human Computer Interface (HCI). HCI AI may include Telerobotics, Human Supervisory Control (e.g., Waypoint Navigation), Brain-Computer Neural Interfaces (e.g., Thought Controlled Devices, Brain Interfaces) and Chatbots (aka Chatterbots) (e.g., AIML).

(6) Note. Artificial Intelligence methods include, but are not limited to: Supervised learning classifiers, unsupervised learning classifiers, reinforcement learning, statistical learning, theorem proving, boosting classifiers, dimensionality reduction, multiresolution analysis, wavelets, quantum AI systems, nanotechnology AI systems, augmented reality systems, pattern recognition systems and automated planning systems.

(7) Note. Artificial Intelligence preprocessing methods include Dimensionality Reduction (reduced feature space, subspace) via Principal Component Analysis (PCA), Kernel Principal Component Analysis (KPCA), Nonlinear Principal component analysis, Independent component analysis (ICA), Singular Value Decomposition (SVD), Eigenface, Kernel Eigenface, Eigenvoice, Kernel Eigenvoice, Self Organizing Map (SOM), Growing Self Organizing Map, Linear Discriminant Analysis (LDA), Fisher's linear discriminant, Linear-Nonlinear Poisson (LNP) Cascade, Multifactor Dimensionality Reduction, Data fusion, Sensor fusion, Image fusion.

(8) Note. Multiresolution Analysis methods include Wavelet transforms, Wavelet series, Wavelet packet, Fast Wavelet Transform, Pyramid generation.

(9) Note. Artificial Intelligence Learning methods fall into three broad categories, namely, Supervised Learning, Unsupervised Learning, and Reinforcement Learning.

(10) Note. Inventive combinations or subcombinations for Supervised Learning Classifiers that may be classified in this class include k-Nearest Neighbor Systems, Fuzzy Logic (e.g., Possibility theory), Neural Networks, Spin Glass Analog Systems, Simulated Annealing, Boltzmann Machines, Vector Quantization, Restricted Coulomb Energy (RCE), Kohonen, Neural Gas, Growing Neural Gas, Pulsed Neural Nets, Support Vector Machines, Maximum Margin Classifiers, Hill-Climbing, Inductive Logic Systems, Bayesian Networks, Belief Networks, Dempster-Shafer Theoretic Network Systems, Gaussian Mixtures, Kriging, Petri Nets (e.g., Finite State Machines, Mealy Machines, Moore Finite State Machines) and Ensembles of Classifiers (e.g., Bagging Systems, Boosting Systems ADABOOST, Classifier trees (e.g., Perceptron trees, Support vector trees, Markov trees, Decision Tree Forests, Random Forests) and Pandemonium Models and Systems.

(11) Note. Inventive combinations or subcombinations for Unsupervised Learning Classifiers that may be classified in this class include Evolutions strategie, Evolutionary Systems, Clustering, Blind Source Separation, Blind Signal Separation, Blind Deconvolution, Self-organizing Maps, Tabu Search.

(12) Note. Inventive combinations or subcombinations for Reinforcement Learning Methods that may be classified in this class include Reinforcement Neural Networks.

(13) Note. Inventive combinations or subcombinations for Artificial Intelligence Learning Hardware can include Memistors, Memristors, Transconductance amplifiers, Pulsed Neural Circuits, Artificially Intelligent Nanotechnology Systems (e.g., Autonomous nanomachines) or Artificially Intelligent Quantum Mechanical Systems (e.g., Quantum Neural Networks).

(14) Note. Inventive combinations or subcombinations for Artificial Intelligence Automatic Pattern Recognition Systems can include Machine Vision Systems, Acoustic Recognition Systems, Handwriting Recognition Systems, Data Fusion Systems, Sensor Fusion Systems, Soft Sensors. Machine Vision Systems can also include Content Based Image Retrieval, Optical Character Recognition, Augmented Reality, Egomotion, Tracking or Optical flow.

(15) Note. Inventive combinations or subcombinations for Automatic Planning and Decision Support Systems can include Emergent systems, Artificially Intelligent Planning, Decision Trees, Petri Nets, Artificially Intelligent Forecasting, which may be properly classifiable in this class.

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370,	Multiplex Communications, subclasses 259 through 271for multiplexed communications enabling three or more terminals to be included in a single call connection.
700,	Data Processing: Generic Control Systems or Specific Applications, subclass 49 for a knowledge processing (e.g., an expert system) adaptive control.
707,	Data Processing: Database, Data Mining, and File Management or Data Structures, subclasses 600 through 606for online analytical processing and decision support in a database environment, subclass 607 for online transactional processing, subclass 608 for collaborative document database and workflow, subclass 637 for optimizing database replication, subclass 665 for rule based database archiving, subclasses 705 through 711 for aspects or search engines in databases, subclasses 723 through 735 for various aspects of ranking search results in the database art, subclasses 736 through 740 for clustering and cataloging in the database art, subclasses 765 through 767 for query refinement and recommending or suggesting search terms, subclasses 776 through 777 for data mining and taxonomy discovery in database arts, subclass 780 for fuzzy search and comparison, subclass 794 for semantic networks, subclasses 797 through 801 for generic data structures.
709,	Electrical Computers and Digital Processing Systems: Multicomputer Data Transferring, subclass 204 for computer conferencing for enabling collaborative processing of data by the computers or digital data processing systems.
715,	Data Processing: Presentation Processing of Document, Operator Interface Processing, and Screen Saver Display Processing, subclasses 733 through 759for concurrently established related or collaborative user interfaces including computer conferencing and computer supported cooperative work.

46	. Knowledge representation and reasoning technique:

This subclass is indented under subclass 45. Subject matter wherein a process or system uses a specific (1) method or system for processing the integrated collection of facts and relationships, (2) inferencing method or system, (3) method or system for interconnecting parts of an expert system, (4) internal or external structured data accessing method or system, or (5) method or system for searching the integrated collection of facts and relationships.

47	.. Rule-based reasoning system:

This subclass is indented under subclass 46. Subject matter comprising an inferencing method or system using logic processing that (1) starts with a set of known facts and applies rules to the facts until no new facts are generated (i.e., forward chaining), or (2) starts with a goal, finds rules to fit the goal, and checks to determine if known facts fit the rules (i.e., backward chaining).

(1) Note. This subclass includes event-driven rule-based reasoning, hypothetical reasoning and rules having priority ordering.

48	... Having specific pattern matching or control technique:

This subclass is indented under subclass 47. Subject matter comprising a system that (1) uses a reticular network algorithm of the collection of facts and relationships, (2) uses a hierarchy of collections (i.e., a higher level integrated collection of facts and relationships about a lower level integrated collection of facts and relationships) or (3) resolves conflicts to determine a firing order for rules.

49	.. Blackboard system:

	This subclass is indented under subclass 46. Subject matter comprising a specific method or system for interconnecting parts of the knowledge processing system and having a special memory (i.e., blackboard) that allows data from one part of the knowledge processing system to be written so that it can be accessed by other parts of the knowledge processing system.

50	.. Having specific management of a knowledge base:

This subclass is indented under subclass 46. Subject matter comprising a specific data accessing method or system (such as a database management or a lookup table) to access a database containing information of the knowledge processing system (i.e., knowledge base).

(1) Note. This subclass includes storage and retrieval (e.g., KBMS, DBMS, content-addressable memory, table, etc.).

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707,	Data Processing: Database, Data Mining, and File Management or Data Structures, appropriate subclasses for information processing system database and file management, per se.

51	.. Non-monotonic reasoning system:

This subclass is indented under subclass 46. Subject matter wherein processing of the integrated collection of facts and relationships contains belief revision (tracking dependencies among propositions).

(1) Note. This subclass includes truth maintenance systems.

52	.. Reasoning under uncertainty (e.g., fuzzy logic):

This subclass is indented under subclass 46. Subject matter wherein the integrated collection of facts and relationships contain inexact knowledge.

(1) Note. This subclass provides for confidence factors, fuzzy logic, membership functions, qualitative reasoning, probabilistic logic, or uncertainty factors.

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1,	for fuzzy logic hardware.
900,	for cross reference art collection of a data processing system having fuzzy logic processing and no fuzzy logic hardware.

53	.. Frame-based reasoning system:

This subclass is indented under subclass 46. Subject matter wherein the integrated collection of facts and relationships (1) is connected in a hierarchy of levels that allow facts or relationships missing in a lower level to be inherited from a connected higher level, (2) uses a set of slots related to a specific object, each slot storing a feature of the object, (3) uses an outline (i.e., a script) of an episode of a certain type, or (4) uses a name of some item (i.e., an object) in either an object attribute-value triplet or an object-attribute pair.

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54,	for knowledge processing system using analogical reasoning.
55,	for knowledge processing system having a semantic network.

54	.. Analogical reasoning system:

This subclass is indented under subclass 46. Subject matter wherein the integrated collection of facts and relationships (1) is in an object having a set of attributer value pairs and (2) has retrieval based on a measure or similarity between query and stored objects.

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53,	for knowledge processing system using frame-based reasoning.

55	.. Semantic network (i.e., conceptual dependency, fact based structure):

This subclass is indented under subclass 46. Subject matter wherein the integrated collection of facts and relationships formalizes object and values as nodes, and connects the nodes with arcs that indicate relationships between the various nodes.

(1) Note. This subclass includes conceptual graphs and connectionist systems.

56	.. Predicate logic or predicate calculus:

This subclass is indented under subclass 48. Subject matter wherein the integrated collection of facts and relationships uses a complex reasoning system formed with symbols (arguments and predicates).

(1) Note. A notation of predicate logic is either xPy or P(x,y)

(2) Note. Predicate logic is usually considered an extension of propositional logic.

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57,	for knowledge processing system having propositional logic.

57	.. Propositional logic:

This subclass is indented under subclass 46. Subject matter wherein the integrated collection of facts and relationships uses a reasoning system formed with truth values (e.g., X is a metal, if C then D) or logic connectives (e.g., and, or, not).

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56,	for knowledge processing system having predicate logic or predicate calculus.

58	.. Temporal logic:

	This subclass is indented under subclass 46. Subject matter wherein the integrated collection of facts and relationships contain data having a representation for an aspect of time.

59	. Creation or modification:

This subclass is indented under subclass 45. Subject matter comprising software or hardware for initially developing or altering a knowledge processing system.

(1) Note. This subclass includes knowledge acquisition techniques.

60	.. Expert system shell or tool:

Subject matter under 59 wherein the software for developing a knowledge processing system (1) provides an interface to a knowledge base or a knowledge processing system or (2) contains an inference engine, a user interface, and knowledge acquisition aids, but no knowledge base (i.e., a "tool").

SEE OR SEARCH CLASS:

715,	Data Processing: Presentation Processing of Document, Operator Interface Processing, and Screen Saver Display Processing, subclasses 700 through 866for a computer operator interface.

61	.. Knowledge acquisition by a knowledge processing system:

This subclass is indented under subclass 59. Subject matter wherein the system automatically adds to its current integrated collection of facts and relationships.

(1) Note. This subclass includes automatic generation of rules or membership functions by a knowledge processing system.

62	MISCELLANEOUS:

	This subclass is indented under the class definition. Subject matter not provided for in any of the preceding subclasses.

900	FUZZY LOGIC:

This subclass is indented under the class definition. Subject matter comprising data processing with inexact reasoning implemented using set membership functions.

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700,	Data Processing: Generic Control Systems or Specific Applications, subclass 50 for adaptive control using fuzzy logic.
701,	Data Processing: Vehicles, Navigation, and Relative Location, subclass 27 for automatic route guidance using fuzzy logic.

902	APPLICATION USING AI HAVING DETAIL OF THE AI SYSTEM:

	This subclass is indented under the class definition. Subject matter comprising an expert system having a specific area of application.

903	. Control:

	This subclass is indented under subclass 902. Subject matter wherein the expert system provides control data.

904	.. Manufacturing or machine (e.g., agriculture machinery, machine tool):

	This subclass is indented under subclass 903. Subject matter wherein the application is related to manufacturing or machinery.

905	.. Vehicle or aerospace:

	This subclass is indented under subclass 903. Subject matter wherein the application is related to a vehicle or aerospace.

906	.. Process plant:

	This subclass is indented under subclass 903. Subject matter wherein the application is related to a process plant.

907	... Power plant:

	This subclass is indented under subclass 906. Subject matter wherein the process plant is a power plant.

908	.. Electronic or computer(internal or network) circuit:

	This subclass is indented under subclass 903. Subject matter wherein the application is related to an electronic circuit, or to the internal operation of a computer or its connection in a network.

909	.. Communication:

	This subclass is indented under subclass 903. Subject matter wherein the application is related to communication.

910	.. Elevator:

	This subclass is indented under subclass 903. Subject matter wherein the application area is related to an elevator.

911	. Nonmedical diagnostics:

	This subclass is indented under subclass 902. Subject matter wherein the expert system provides nonmedical diagnostic data.

912	.. Manufacturing or machine (e.g., agriculture machinery, machine tool):

	This subclass is indented under subclass 911. Subject matter wherein the application is related to manufacturing or machinery).

913	.. Vehicle or aerospace:

	This subclass is indented under subclass 911. Subject matter wherein the application is related to a vehicle or aerospace.

914	.. Process plant:

	This subclass is indented under subclass 911. Subject matter wherein the application is related to a process plant.

915	... Power plant:

	This subclass is indented under subclass 914. Subject matter wherein the process plant is a power plant.

916	.. Electronic or computer (internal or network) circuit:

	This subclass is indented under subclass 911. Subject matter wherein the application is related to an electronic circuit, or to the internal operation of a computer or its connection in a network.

917	.. Communication:

	This subclass is indented under subclass 911. Subject matter wherein the application is related to communication.

918	.. Elevator:

	This subclass is indented under subclass 911. Subject matter wherein the application area is related to an elevator.

919	. Designing, planning, programming, CAD, CASE:

	This subclass is indented under subclass 902. Subject matter wherein the expert system provides data related to designing of an object, plan preparation, program preparation, computer aided design (i.e., CAD), or computer aided software engineering (i.e., CASE).

920	.. Simulation:

	This subclass is indented under subclass 919. Subject matter wherein the expert system provides simulation related data, e.g., three-dimensional computer simulation of a piston of a car on a computer screen.

921	.. Layout (e.g., circuit, construction):

	This subclass is indented under subclass 919. Subject matter wherein the expert system provides layout related data, e.g. computer circuit layout or building layout.

922	.. Computer program preparation:

	This subclass is indented under subclass 919. Subject matter wherein the expert system provides computer program preparation related data.

923	.. Construction:

	This subclass is indented under subclass 919. Subject matter wherein the expert system provides data related to construction industry, e.g., building codes.

924	. Medical:

	This subclass is indented under subclass 902. Subject matter wherein the expert system provides medical related data.

925	. Business:

	This subclass is indented under subclass 902. Subject matter wherein the expert system provides business related data.

926	.. Time management:

	This subclass is indented under subclass 925. Subject matter wherein the data is time management data.

927	. Education or instruction:

	This subclass is indented under subclass 902. Subject matter wherein the expert system provides education or instruction data.

928	. Earth science:

	This subclass is indented under subclass 902. Subject matter wherein the expert system provides earth related science data.

929	.. Geological (e.g., seismology):

	This subclass is indented under subclass 928. Subject matter wherein the expert system provides geology related data.

930	.. Environment:

	This subclass is indented under subclass 928. Subject matter wherein the expert system provides environment related data.

931	... Weather:

	This subclass is indented under subclass 930. Subject matter wherein the data is weather data.

932	. Mathematics, science, or engineering:

	This subclass is indented under subclass 902. Subject matter wherein the expert system provides mathematics, science or engineering related data.

933	. Law, law enforcement, or government:

	This subclass is indented under subclass 902. Subject matter wherein the expert system provides law, law enforcement, or government related data.

934	. Information retrieval or information management:

	This subclass is indented under subclass 902. Subject matter wherein the expert system provides information retrieval or information management related data.

FOR000

CLASS-RELATED FOREIGN DOCUMENTS

	This subclass has no definition.

FOR 100

ARTIFICIAL INTELLIGENCE:

	Foreign art collection including subject matter wherein the system or method has the capacity to perform one or more of the functions of recognition, speech signal processing, knowledge processing (i.e., propositional logic, reasoning, learning, self-improvement), complex operations of a manipulator (e.g., robot* control), or inexact reasoning (e.g., fuzzy logic).

FOR 101

. Fuzzy logic hardware:

	Foreign art collection including subject matter wherein the system includes a specific circuit arrangement for performing logic with more than two levels, e.g., nonbinary or analog logic systems.

FOR 102

. Knowledge processing:

Foreign art collection including subject matter wherein the system or method (1) has the capacity to process knowledge (i.e., data comprised of an integrated collection of facts and relationships), (2) has the capacity to generate its own set of rules (e.g., trainable processors), (3) structurally duplicates the human brain (e.g., neural networks), (4) functionally duplicates a law of nature (e.g., inheritance, evolution, etc.), or (5) has the capacity for solution of problems in these areas.

FOR 103

.. Plural processing systems:

	Foreign art collection including subject matter comprising two or more systems, or methods utilizing two or more systems, wherein at least one system is a knowledge processing system.

FOR 104

.. Graphical or natural language user interface:

	Foreign art collection including subject matter wherein presentation of data to the user of the system includes nonverbal representations or symbols, or statements in standard English language syntax.

FOR 105

.. Genetic algorithms:

	Foreign art collection including subject matter wherein the system uses a sequence of steps that (1) starts with a group of solutions to a problem, (2) represents each solution as a coded data string, (3) divides and splices the coded numerical strings to create new solutions, and (4) determines the fitness of the new solutions.

FOR 106

.. Trainable (i.e., adaptive) systems:

	Foreign art collection including subject matter wherein (1) the system creates its own set of rules (i.e., connection weights) (e.g., learns by example) or wherein (2) the data processing method involves in any way a system which creates its own set of such rules.

FOR 107

... Neural networks:

	Foreign art collection including subject matter wherein the system uses parallel distributed processing processors constructed in hardware or simulated in software. 800.01+, (see (1) Note, above).

FOR 108

.... Connectionist expert systems:

	Foreign art collection including subject matter wherein the parallel distributed processing processors have been trained to be an expert system, that is, to process data formed by an integrated collection of facts and relationships (i.e., knowledge).

FOR 109

.... Training (i.e., programming or learning):

	Foreign art collection including subject matter wherein a specific method or apparatus is used to adjust the rules (i.e., connection weights).

FOR 110

.... Structures:

	Foreign art collection including details of the construction of the processing processors or their interconnections.

FOR 111

..... Radiant energy type (e.g., optical):

	Foreign art collection including subject matter wherein the structure includes a source or detector of radiant wave energy.

FOR 112

..... Sequential processor:

	Foreign art collection including subject matter wherein the structure comprises one or more computers that process software step-by-step.

FOR 113

..... Including a digital or binary element:

	Foreign art collection including subject matter wherein the structure includes a processing component that can assume only two values.

FOR 114

.. Expert systems:

	Foreign art collection including subject matter comprising a system wherein the data consists of an integrated collection of facts and relationships (i.e., knowledge).

FOR 115

... Deduction, control, or search techniques:

Foreign art collection including subject matter wherein a process or system uses a specific (1) method or system for processing the integrated collection of facts and relationships, (2) inferencing method or system, (3) method or system for interconnecting parts of the expert system, (4) internal or external structured data accessing method or system, or (5) method or system for searching the integrated collection of facts and relationships.

FOR 116

.... Forward or backward chaining:

Foreign art collection including an inferencing method or system using logic processing that starts with a set of known facts and applies rules to the facts until no new facts are generated or a goal is reached (i.e., forward chaining), or logic processing that starts with a goal and then finds rules to fit the goals and then checks to see if known facts fit the found rules (i.e., backward chaining).

FOR 117

.... Blackboarding:

	Foreign art collection including subject matter wherein a specific method or system for interconnecting parts of the expert system uses a special memory (i.e., blackboard) where data from one part of the expert system can be written so that it can be accessed by other parts of the expert system.

FOR 118

.... Knowledge base accessing (e.g., DBMS, table):

	Foreign art collection including subject matter wherein a specific data accessing method or system, such as a database management system or a lookup table, is used to access a database containing the knowledge of the expert system (i.e., the knowledge base).

FOR 119

.... Truth maintenance systems (TMS):

	Foreign art collection including subject matter wherein the processing of the integrated collection of facts and relationships include belief revision by tracking dependencies among propositions and informing a user as to which propositions can be believed.

FOR 120

... Knowledge representations:

	Foreign art collection including subject matter wherein a process or system uses (1) a specific type of relationship in the integrated collection of facts and relationships, (2) a specific type of integrated collection of facts and relationships, or (3) a specific type of fact in the integrated collection of facts and relationships.

FOR 121

.... For inexact knowledge (e.g., fuzzy logic):

	Foreign art collection including subject matter wherein the facts or relationships include a weight value other than 1 (e.g., 1/2, .5, 1.5, 60%).

FOR 122

.... Objects (i.e., object-attribute-value), frames and slots, or scripts:

Foreign art collection including subject matter wherein the specific integrated collection of facts and relationships uses (1) a set of slots (i.e., a frame) related to a specific object, each slot storing a feature of the object, (2) an outline (i.e., a script) of an episode of a certain type, or (3) the name of some item (i.e., an object) in either an object-attribute-value triplet or an object-attribute pair.

FOR 123

.... Semantic network (i.e., conceptual dependency, fact based structure):

	Foreign art collection including subject matter wherein the specific integrated collection of facts and relationships formalizes objects and values as nodes, and connects the nodes with arcs or links that indicate the relationships between the various nodes.

FOR 124

.... Rete network or meta-knowledge:

Foreign art collection including subject matter which (1) uses a reticular network algorithm on the collection of facts and relationships (e.g., is formed of subcollections which are searched in parallel) or (2) includes a hierarchy of collections, i.e., a higher level integrated collection of facts and relationships about a lower level integrated collection of facts and relationships (i.e., knowledge about knowledge).

FOR 125

.... Inheritance:

	Foreign art collection including subject matter wherein the specific integrated collection of facts and relationships is connected in a hierarchy of levels which allow facts or relationships missing in a lower level to be taken (i.e., inherited) from a connected higher level where they are present.

FOR 126

.... Predicate logic or predicate calculus:

	Foreign art collection including subject matter wherein the specific integrated collection of facts and relationships uses a complex logic system formed with arguments and predicates.

FOR 127

.... Propositional logic:

	Foreign art collection including subject matter wherein the specific integrated collection of facts and relationships uses a simple logic formed with truth values (e.g., "X is a metal," "if C then D") or logic connectives (e.g., and, or, not).

FOR 128

.... History base:

	Foreign art collection including subject matter wherein the specific integrated collection of facts and relationships include historical data (i.e., data collected over a period of time) about the expert system or about the area of expertise.

FOR 129

... Creation or modification of an expert system:

	Foreign art collection including subject matter comprising means (i.e., software or hardware) for initially developing or altering the expert system.

FOR 130

.... Expert system shells or tools:

	Foreign art collection including subject matter wherein the software for developing an expert system (1) contains an inference engine, a user interface, and knowledge acquisition aids, but no knowledge base (i.e., a "tool") or (2) provides an interface to such a tool or an expert system (i.e., a "shell").

FOR 131

.... Learning or knowledge acquisition by the expert system:

	Foreign art collection including subject matter wherein the existing expert system has the capability to automatically add to its current integrated collection of facts and relationships.