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Knowledge-based systems Tutorial

Knowledge-based systems Tutorial. Introduction to G2 Rozália Lakner University of Veszprém Department of Computer Science. Contents. Main characteristics of G2 Main components of G2 knowledge base Reasoning in G2 Development of knowledge base . Main characteristics of G2.

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Knowledge-based systems Tutorial

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  1. Knowledge-based systemsTutorial Introduction to G2 Rozália Lakner University of Veszprém Department of Computer Science

  2. Contents • Main characteristics of G2 • Main components of G2 knowledge base • Reasoning in G2 • Development of knowledge base

  3. Main characteristics of G2

  4. G2 – a real-time expert system • used for rapid prototyping and implementing expert systems • G2 possess features and properties of an expert system shell • user-friendly interfaces • well-structured natural language in a high-level • graphic-oriented environment • inference engine (and simulator) • forward and backward reasoning • elements of knowledge base (items) • objects, workspaces, connections, relations, variables, parameters, rules, procedures, functions • tools for developing knowledge base

  5. Main components of G2 knowledge base

  6. G2 - Objects • representation of some part of the application • water-tank, valve, coffee-machine • picture of each object: icon • generated manually (permanent objects) • has a table of attributes (contains the knowledge about the object) • object classes • attributes, icon are inherited • own specific attributes • object hierarchy • actual application objects: instances

  7. Variables, parameters • built-in object classes • represent things that have changing values • temperature, level, … • similarities • attributes, classes, icon, history keeping • differences • a value of a variable may expire • a parameter always has current value (initial value) • a variable has validity interval • data-seeking sources for variable’ value • internal data server • inference engine (backward changing) • G2 simulator

  8. Workspaces • rectangular areas • can contain items (objects, connections, rules, …) • workspace-hierarchy • enabling/disabling workspaces • permanent/temporary workspaces

  9. Connections, relations • connection • relationship between objects (created manually) • graphically links two objects together (flow-pipe, electrical wire) • represents abstract relationship (partnership, ownership) • classes of connections • objects can be referred based on connection • possible to write generic rules (any tank connected to any valve) • relation • relationship between objects (created dynamically, „conclude” action) • classes of relations • has not graphical representation • doesn’t saved as part of a knowledge base

  10. Rule types 1 • If rules (common rules) for any valve V if the state of V = 1 then change the center stripe-color of every flow-pipe connected to V to sky-blue • When rules (cannot be used in reasoning) for any container-or-vessel CV when the value of the inventory of CV = 0 then conclude that the temperature of CV has no value • Initial rules (invoked when KB starts or restarts) initiallyfor any container-or-vessel CV if the inventory of CV > 0 then conclude that the temperature of CV = 15

  11. Rule types 2 • Unconditional rules (rules without condition part) initiallyfor any valve V unconditionally conclude that the state of V = 0 • Whenever rules (event-controlled rules) whenever auto-manual-state receives a value and when the value of auto-manual-state is auto then start auto()

  12. Main attributes of rules • options (how can use the rule) • scan interval (how often to invoke the rule) • rule priority (in case of overloading) • depth-first backward chaining precedence (conflict resolution) • timeout for rule completion (how long G2 may try to evaluate the condition part)

  13. Procedures • sequence of operations executed by G2 • like high-level procedural languages • main part of procedures • procedure header (name, typed argument list, return type) • local declarations • procedure body (begin, sequence of procedure statements, end)

  14. Reasoning in G2

  15. Real-time inference engine 1 • functions of inference engine (IE): • reasons about the current state of the application • communicates with the end-user • iniciates other activity based upon what it has inferred • IE operates on the following sources of information: • the knowledge contained in the knowledge base • simulated values • values received from sensors and other external sources

  16. Real-time inference engine • abilities of IE: • scan rules: repeatedly invoke a rule at regular time interval (scan interval) • wakeup rules: when a variable receives a value, the inference engine wakes up the rule that was waiting for the value of the variable • data seeking: get value from the specified data server (when the value of the variable is expired) • chaining the rules (reasoning) • backward chaining: IE infers the value of a variable with the help of rules (when the value of a variable is not given by a sensor or a formula) • forward chaining: IE invoke a rule when its condition part is satisfied by another rule

  17. G2 simulator • special data server in G2

  18. Development of knowledge-base

  19. Developer interface • graphic-oriented environment • creating the model of the application graphically (schematic) • objects are represented by icons • objects are placed in workspaces • objects are connected graphically • pop-up menus for objects (attribute table, delete, change size and colour, move, …)

  20. Developer interface 2 • well-structured natural language in a high-level • referring to an item: • by name: coffee-machine • by class name: the vessel • as an instance of a class is nearest to another item on schematic: the level-icon nearest to coffee-machine • as an instance of a class that is connected to an object by an input or output connection: the valve connected at the output of coffee-machine

  21. Developer interface 3 • interactive text editor • text-edit workspace • inserting text from other items or scrapbook • syntax-checking • marking incorrect text • warning message • suggestion for correction

  22. Developer interface • interactive icon editor • graphic tool • design icons graphically • converting into G2 grammar • layers, regions • main parts of icon editor • icon view • buttons for creating graphic elements • icon size display • cursor location display • layer pad and layer display

  23. Developer interface 5 • tools for managing large KBs • clone objects and statements • operate on a group of objects • inspect utility (browse KB) – finding items easy • describe facility (informations about item) – data server, rules • organize knowledge hierarchically (workspaces, subworkspaces, activate/ deactivate) • merge KBs

  24. Developer interface 6 • documentation in KB: free texts (only for documentation, is not part of KB) • tracing and debugging facilities • warning messages (errors, unusual conditions) • trace messages • current value of variable, expression (each time it receives one) • starting and finishing time of evaluating of variable, formula, rule, procedure, function • set breakpoints • highlight invoked rules • access control facilities • restrict the choices a user has on the menus • restrict moving items, making connections, … • restrict accessing to the attribute table • restrict editing of attributes • mode of operation (specify restrictions): operator, administrator, developer, …

  25. User interface 1 • displays • screen items showing the value of variable, parameter, expression • end-user controls • control an application by the user • messages, message board • items that display text • are used for communication

  26. User interface • displays • readout table • variable, parameter and its value • chart • plots of one or more variables • history of values change over time • meter • value of variable in a vertical display • dial • value of variable in a round scale • freeform table • tabular form of variable’s values • end-user controls • messages, message board

  27. User interface • end-user controls • action buttons • execute an action (start, conclude, show, …) • radio buttons • assign a predefined value for variable or parameter • check box • assign „on” or „off” value for variable or parameter • slider • enter numeric value for variable or parameter by sliding a pointer • type-in box • enter a value for variable or parameter from keyboard

  28. G2 – Aplication examples ABB Power -- expert monitoring and diagnostics of power plant processes Ashland Petroleum -- expert monitoring and optimization of energy systems. Ford Motor Company -- expert control of flexible manufacturing systems. Lafarge -- expert control of cement kilns for improved throughput, reduced energy costs, and reduced equipment maintenance. =>25 plants Petrobras -- expert operator advisory systems for optimizing power generation and distribution. Seagate Technology -- expert monitoring, diagnosis, and operator advice improves yields of disk-drive manufacturing. Shell Expro -- expert optimization pumps up oil field production. http://www.gensym.com/manufacturing/g2_success.shtml

  29. G2/ Intelligent Objects • Knowledge modules for monitoring and operation of process equipment: • Fired Heaters • Compressors • Columns • Treaters • Pumps • Heat Exchangers • Sensors • Analyzers • Controllers • Tanks • Vessels Intelligent Objects deliver configurable equipment knowledge out-of-the-box, and can be readily extended for plant-specific requirements. Proactive Detection of Equipment Problems - Intelligent Objects proactively monitor equipment conditions to detect problems early and alert operators to take action - before the problem reaches the alarm limits of a traditional process control system Rapid Deployment - Deployment time for a first Intelligent Object is rapid - it can typically be ready to go online within weeks for complex equipment, such as a fired heater or a compressor, and in days for basic equipment, such instruments, vessels, heat exchangers, or controllers. Unit and Plant Wide Diagnostic Capability - Intelligent Objects can work together to provide automated diagnosis of process problems that are impacting an entire unit or plant.

  30. Optegrity • Optegrity is a platform from Gensym for rapidly developing and deploying abnormal condition management applications in the process manufacturing industries • Applications built on the Optegrity platform work in real time using information from existing control systems, data historians and databases to: • Proactively monitor process conditions throughout a production unit or plant to detect problems early in order to avoid or minimize disruptions • Analyze, filter and correlate alarms to speed up operator responses • Rapidly isolate the root cause of unit and plant wide problems to accelerate resolution • Guide operators through recovery to enhance safety levels while effectively responding to problems • Predict the impact of process disruptions so operators can prioritize actions NeurOn-Line Gensym's NeurOn-Line platform delivers neural network applications that improve process performance by predicting quality and process conditions in real time. With NeurOn-Line, engineers quickly build and deploy neural network models based on historical process data that capture the relationships between product quality and process conditions.

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