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Learn about knowledge representation schemes like logical, procedural, structured, and networked, and understand how they contribute to intelligence.
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Knowledge representation Intelligence requires • the ability to represent information about the world, and • the ability to reason with the information • knowledge representation schemes • logical: use formal logic to represent knowledge - PL, FOPL • procedural: knowledge as a set of instructions for solving a problem - rule based • structured: - frames, conceptual dependencies, scripts • Networked - knowledge as objects/concepts and their associations - semantic nets, conceptual graphs
Frames (Minsky, 1975) A frame is like a record that contains information relevant to stereotyped action or entity: • Frame Identification • Record like structure consists of collection of slots and slot values. • Slots may be of any type and size. It has names and values called facets, facet also have names and values. • Slots specify general or specific characteristics of the entity for which frame • represents. • Slot contains attribute-value pairs, default values, conditions, pointer to other frames, procedures. Frames have labeled slots with slot contents an object or action and slot labels are the role played by the slot filler in relation to the central entity of action.
“there is a particular type of car called a VW, manufactured in Germany.” Name: VW Subclass of: car Slots: Name: Value: Restrictions: made in Germany
Frames • All the information relevant to a particular concept is stored in a single complex entity, called a frame. • Frames support inheritance. • similar to semantic nets, can perform hierarchical lookup • if desired slot exists, get filler • if not, follow link to parent frame and recursively look there • the structured nature of frames makes them easier to extend • can include default values for slots • can specify constraints on slots • can attach procedures to slots
Example Mammal subclass: Animal warm_blooded: yes Elephant subclass: Mammal * colour: grey * size: large Clyde instance: Elephant color: pink owner: Fred
Lisp functions to handle frames • (f-get f-name slot-name, facet-name) - returns data from specified location • (f-slots f-name) - returns names of slots • (f-facets f-name f-slot) - returns names of facets • (f-put f-name slot– n facet– n) - adds data to specified location • (f-remove f-name slot-name facet-name) - remove data.
Conceptual dependency theory (Schank, 1973) • attempts to model the semantic structure of natural language • Based on the use of limited no. of primitives and rules to represent statements • Made up of 5 building blocks • Entities • Actions • Conceptual Cases • Conceptual Tenses • Basic Syntax Rules . . .
Conceptual dependency theory • Entities • Picture Produces – actor or physical objects that perform different actions • Picture Aiders – supporting properties • Actions • ATRANS - transfer of an abstract entity (give) • ATTEND - attention of an object (listen) • CONC - think about something • EXPEL - expulsion of anything from the body (cry) • GRASP - holding an object (clutch) • INGEST - ingesting something (eat) • INBUILD - building an information (tell) • PROPEL - application of force (push) • PTRANS - physical transfer from one location to another (go) • SPEAK - emitting a sound (say)
Conceptual dependency theory • 3. Conceptual cases : • a. Objective case • b. Directive • c. Instrumental • d. Recipient • 4. Conceptual Tenses : • a. Future (f) • b. Past (p) • c. Present (nil) • d. Conditional (c) • e. Transition (t)
CD structures and corresponding syntax for example sentences
conceptual dependency relationships tense/mode modifiers p past f future t transition ? interrogative / negative . . .
Scripts a script is a structure that describes a stereotyped sequence of events in a particular context • closely resembles a frame, but with additional information about the expected sequence of events and the goals/motivations of the actors involved • A script is a data structure used to represent a sequence of events. • Scripts are used for interpreting stories. • A script is composed of • Entry condition - Basic conditions that must be fulfilled. • Scenes - Sequence of activities • Properties - Objects that are existing in the script • The actors - Agents that can change the state of the world • Acts: A set of actions by the actors. • Results – explains what happens after the script has occurred.
Semantic nets (Associative Network) Quillian (1967) introduced semantic networks while others (Simmons -1973, Brachman-1979, Schank-1979) have extended the model. • Semantic Network representations provide a networked knowledge representation.
Semantic Nets • A semantic net is represented as a graph, where the nodes in the graph represent concepts, • and the arcs represent binary relationships between concepts. • Nodes represent objects, attributes and values • Links represent attributes and relationships between nodes • Labels attached to links: the name of the corresponding attribute or relation
Semantic Net Syntax • The language of semantic net contains letters of alphabets, relational symbols, set membership, subset symbols, decimal digits, square and oval nodes, and directed arcs “instance of” - set membership • “Nodes used for objects or nouns, arcs for relation • Relation – ISA, MEMBER – OF SUBSET OF , AKO, HAS – PART, INSTANCE – OF
Property of Inheritance More specific (sub)classes inherit (get) properties from more general (super)classes through is_a / is_instance_of links
semantic nets & inheritance in addition to data retrieval, semantic nets can provide for deduction using inheritance • since a canary is a bird, it inherits the properties of birds (likewise, animals) • e.g., canary can fly, has skin, … • to determine if an object has a property, • look for the labeled association, • if no association for that property, follow is_a link to parent class and (recursively) look there
Applications ontologies, relational networks Example: http://www.troubleshooters.com/tpromag/199907/_model.htm Using Semantic Nets to Model Troubleshooting's Knowledge
Conceptual Graphs • A conceptual graph is a refinement of semantic networks. • A conceptual graph is bipartite with concepts and conceptual relationships. • Concept refers to entities, actions, properties and events. • Conceptual Relationship node represents relation between concepts. • It does not use labels for arcs. • If it is individual the concept written as type field followed by referent field.
Conceptual Graphs - Examples Conceptual graph for “John is eating Candy” Textual representation of “Tweety ate a fat worm”
Conceptual Graph Examples flies bird dog color brown mother child parents father agent mary give object book recipient john