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Match each Artificial Intelligence term in List-I that best describes a given situation in List-II :

$\begin{array}{clcl}  &  \textbf{List-I} && \textbf{List-II} \\ \text{I.} & \text{Semantic Network} & \text{a.} & \text{Knowledge about what to do as} \\ &&& \text{opposed to how to do it} \\  \text{II.} & \text{Frame} & \text{b.} & \text{A premise of rule that is not concluded} \\ &&& \text{by any rule} \\ \text{III.} & \text{Declarative Knowledge} & \text{c.} & \text{A method of knowledge representation that} \\ &&& \text{uses a graph} \\ \text{IV.} & \text{Primitive} & \text{d.} & \text{A data structure representing stereotypical} \\ &&&  \text{knowledge} \\ \end{array}$

$\textbf{Codes :}$

  1. $\text{I-d, II-a, III-b, IV-c}$
  2. $\text{I-d, II-c, III-a, IV-b}$
  3. $\text{I-d, II-c, III-b, IV-a}$
  4. $\text{I-c, II-d, III-a, IV-b}$
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   ans is  D 

semantic net (or semantic network) is a knowledge representation technique used for propositional information. So it is also called a propositional net. Semantic nets convey meaning. They are two dimensional representations of knowledge. Mathematically a semantic net can be defined as a labelled directed graph.

Semantic nets consist of nodes, links (edges) and link labels. In the semantic network diagram, nodes appear as circles or ellipses or rectangles to represent objects such as physical objects, concepts or situations. Links appear as arrows to express the relationships between objects, and link labels specify particular relations. Relationships provide the basic structure for organizing knowledge. The objects and relations involved need not be so concrete. As nodes are associated with other nodes semantic nets are also referred to as associative nets.

A frame is an artificial intelligence data structure used to divideknowledge into substructures by representing "stereotyped situations." Frames are the primary data structure used in artificial intelligence frame languages.

Frames are also an extensive part of knowledge representation and reasoning schemes. Frames were originally derived from semantic networks and are therefore part of structure based knowledge representations. According to Russell and Norvig's "Artificial Intelligence, A Modern Approach," structural representations assemble "...facts about particular object and even types and arrange the types into a large taxonomic hierarchy analogous to a biological taxonomy."

Declarative knowledge involves knowing THAT something is the case - that J is the tenth letter of the alphabet, that Paris is the capital of France. Declarative knowledge is conscious; it can often be verbalized.  Metalinguistic knowledge, or knowledge about a linguistic form, is declarative knowledge.

Procedural knowledge involves knowing HOW to do something - ride a bike, for example. We may not be able to explain how we do it.  Procedural knowledge involves implicit learning, which a learner may not be aware of, and may involve being able to use a particular form to understand or produce language without necessarily being able to explain it.

 Primitive knowledge is knowledge that is defined explicitly by facts.   Derived knowledge is knowledge that can be inferred from other knowledge. Derived knowledge is usually specified in terms of rules.

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