Category: ‘Knowledge Representation’

PostHeaderIcon What is Knowledge?

Knowledge is the body of facts and principles. Knowledge can be language, concepts, procedures, rules, ideas, abstractions,places,customs, and so on. study of knowledge is called Epistemology.

Types of knowledge

The types of knowledge include procedural knowledge, declarative knowledge and heuristic knowledge.

Procedural knowledge

Procedural knowledge is compiled or processed form of information. Procedural knowledge is related to the performance of some task. For example, sequence of steps to solve a problem is procedural knowledge.

Declarative knowledge

Declarative knowledge is passive knowledge in the form of statements of facts about the world. For example, mark statement of a student is declarative knowledge.

Heuristic knowledge

Heuristics knowledge are rules of thumb or tricks. Heuristic knowledge is used to make judgments and also to simplify solution of problems. It is acquired through experience. An expert uses his knowledge that he has gathered due to his experience and learning.

Importance of knowledge

Intelligence requires knowledge. That is, to exhibit intelligence, knowledge is required. Knowledge plays a major role in building intelligent systems.

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Artificial Intelligence – An Overview

PostHeaderIcon Frames

What are Frames?

Natural language understanding requires inference i.e., assumptions about what is typically true of the objects or situations under consideration. Such information can be coded in structures known as frames.

Need of frames

Frame is a type of schema used in many AI applications including vision and natural language processing. Frames provide a convenient structure for representing objects that are typical to a stereotypical situations. The situations to represent may be visual scenes, structure of complex physical objects, etc. Frames are also useful for representing commonsense knowledge. As frames allow nodes to have structures they can be regarded as three-dimensional representations of knowledge.

A frame is similar to a record structure and corresponding to the fields and values are slots and slot fillers. Basically it is a group of slots and fillers that defines a stereotypical object. A single frame is not much useful. Frame systems usually have collection of frames connected to each other. Value of an attribute of one frame may be another frame.

A frame for a book is given below.

Slots Fillers
publisher Thomson
title Expert Systems
author Giarratano
edition Third
year 1998
pages 600

The above example is simple one but most of the frames are complex. Moreover with filler slots and inheritance provided by frames powerful knowledge representation systems can be built.

Frames can represent either generic or frame. Following is the example for generic frame.

Slot Fillers
name computer
specialization_of a_kind_of machine
types (desktop, laptop,mainframe,super)
if-added: Procedure ADD_COMPUTER
speed default: faster
if-needed: Procedure FIND_SPEED
location (home,office,mobile)
under_warranty (yes, no)

The fillers may values such as computer in the name slot or a range of values as in types slot. The procedures attached to the slots are called procedural attachments. There are mainly three types of procedural attachments: if-needed, default and if-added. As the name implies if-needed types of procedures will be executed when a filler value is needed. Default value is taken if no other value exists. Defaults are used to represent commonsense knowledge. Commonsense is generally used when no more situation specific knowledge is available.

The if-added type is required if any value is to be added to a slot. In the above example, if a new type of computer is invented ADD_COMPUTER procedure should be executed to add that information. An if-removed type is used to remove a value from the slot.

PostHeaderIcon Semantic Nets

A 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.

Figure: A Semantic Network

Figure: A Semantic Network

In the above figure all the objects are within ovals and connected using labelled arcs. Note that there is a link between Jill and FemalePersons with label MemberOf. Simlarly there is a MemberOf link between Jack and MalePersons and SisterOf link between Jill and Jack. The MemberOf link between Jill and FemalePersons indicates that Jill belongs to the category of female persons.

Inheritance Reasoning

Unless there is a specific evidence to the contrary, it is assumed that all members of a class (category) will inherit all the properties of their superclasses. So semantic network allows us to perform inheritance reasoning. For example Jill inherits the property of having two legs as she belongs to the category of FemalePersons which in turn belongs to the category of Persons which has a boxed Legs link with value 2. Semantic nets allows multiple inheritance. So an object can belong to more than one category and a category can be a subset of more than one another category.

Inverse links

Semantic network allows a common form of inference known as inverse links. For example we can have a HasSister link which is the inverse of SisterOf link.The inverse links make the job of inference algorithms much easier to answer queries such as who the sister of Jack is. On discovering that HasSister is the inverse of SisterOf the inference algorithm can follow that link HasSister from Jack to Jill and answer the query.

Disadvantage of Semantic Nets

One of the drawbacks of semantic network is that the links between the objects represent only binary relations. For example, the sentence Run(ChennaiExpress, Chennai,Bangalore,Today) cannot be asserted directly.

There is no standard definition of link names.

Advantages of Semantic Nets

Semantic nets have the ability to represent default values for categories. In the above figure Jack has one leg while he is a person and all persons have two legs. So persons have two legs has only default status which can be overridden by a specific value.

They convey some meaning in a transparent manner.

They nets are simple and easy to understand.

They are easy to translate into PROLOG.