Knowledge Representation Issues

Knowledge Representation Issues

Representation Mappings

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Knowledge Representation Issues

Representation Mappings

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Knowledge Representation Issues

Representation Mappings

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Knowledge Representation Issues

Representation Mappings

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Knowledge Representation Issues

Representation Mappings

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Knowledge Representation Issues

Representation Mappings

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Knowledge Representation Issues

Representation Mappings

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Knowledge Representation Issues

Representation Mappings

• The dotted line across the top represents the abstract reasoning process that a program is intended to model.
• The solid line across the bottom represents the concrete reasoning process that a particular program performs.
• This program successfully models the abstract process to the extent that, when the backward representation mapping is applied to the program’s output, the appropriate final facts are actually generated.
• If either the program’s operations or one of the representation mappings is not faithful to the problem that is being modelled, then the final facts will probably not be the desired ones.
• If no good mapping can be defined for a problem, then no matter how good the program to solve the problem is, it will not be able to produce answers that correspond to real answers to the problem.

Knowledge Representation Issues

Approaches to knowledge representation:

A good system for the representation of knowledge in a particular domain should possess the following four properties:

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Knowledge Representation Issues

Approaches to knowledge representation:

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Knowledge Representation Issues

Approaches to knowledge representation:

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Knowledge Representation Issues

Inheritable knowledge :

• To a set of attributes and associated values that together describe the objects of the knowledge base.
• Knowledge about objects, their attributes, and their values need not be as simple as that shown in our example.
• It is possible to increase the basic representation with inference mechanisms that operate on the structure of the representation.
• The structure must be designed to correspond to the inference mechanisms that are desired.
• One of the most useful forms of inference is property inheritance, in which elements of specific classes inherit attributes and values from more general classes in which they are included.

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Knowledge Representation Issues

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Knowledge Representation Issues

• In order to support property inheritance, objects must be organized into classes and classes must be arranged in a generalization hierarch.
• Some additional baseball knowledge inserted into a structure that is so arranged.
• Lines represent attributes, Boxed nodes represent objects and values of attributes of objects.
• These values can also be viewed as objects with attributes and values..
• The arrows on the lines point from an object to its value along the corresponding attribute line, the structure shown in the figure is a slot and filler structure.
• It may also called a semantic n/w or a collection of frames.
• Each individual frame represents the collection of attributes and values associated with a particular node.

Knowledge Representation Issues

• All of the objects and most of the attributes shown in this example have been chosen to correspond to the baseball domain, and they have no general significance.
• The two exceptions to this are the attribute isa, which is being used to show class inclusion, and the attribute instance, which is being used to show class membership.
• The two specific attributes provide the basis for property inheritance as an inference technique.
• Using this technique the knowledge base can support retrieval both of facts that have been explicitly stored and of facts that can be derived from those that are explicitly stored.

Knowledge Representation Issues

Knowledge Representation Issues

Knowledge Representation Issues

Inferential knowledge:

Property inheritance is a powerful of inheritance, but it is not the only form.

All the power of traditional logic is necessary to describe the inference that are needed.

The below two examples of the use of first-order predicate logic to represent additional knowledge about baseball.

Knowledge Representation Issues

Procedural knowledge:

• The above examples of baseball knowledge have concentrated on relatively static, declarative facts.
• It is equally useful, kind of knowledge is operational or procedural knowledge that specifies what to do when procedural knowledge can be represented in programs in many ways.
• The most common way is simply as code for doing something.
• The machine uses the knowledge when it executes the code to perform a task.
• The way representing procedural knowledge gets low scores with respect to the properties of inferential adequacy and acquisitional efficiency.
• The most commonly used technique for representing procedural knowledge in AI programs is the use of production rules.

Knowledge Representation Issues

Issues in Knowledge Representation:

Before going to discussion of specific mechanisms that have been used to represent various kinds of real-world knowledge, we need briefly to discuss several issues that across all of them:

• Are any attribute of objects so basic that they occur in almost every problem domain? If there are, we need to make sure that they are handled appropriately in each of the mechanisms we propose. If such attributes exist, when are they?
• Are there any important relationships that exist among attributes of objects?
• At what level should knowledge be represented? Is there a good set of primitives into which all knowledge can be broken down? Is it helpful to use such primitives?
• How should sets of objects be represented?
• Given a large amount of knowledge stored in a database, how can relevant parts be accessed when they are needed?

Knowledge Representation Issues

Issues in Knowledge Representation:

• Important Attribute
• Relationships among Attributes.
• Choosing the granularity of representation
• Representing sets of objects
• Finding the right structures as needed

Knowledge Representation Issues

Issues in Knowledge Representation:

Knowledge Representation Issues

Issues in Knowledge Representation:

Knowledge Representation Issues

Issues in Knowledge Representation:

Knowledge Representation Issues

Issues in Knowledge Representation:

Knowledge Representation Issues

Issues in Knowledge Representation:

Knowledge Representation Issues

Issues in Knowledge Representation:

Knowledge Representation Issues

Issues in Knowledge Representation:

Knowledge Representation Issues

Issues in Knowledge Representation:

Knowledge Representation Issues

Issues in Knowledge Representation:

Knowledge Representation Issues

Issues in Knowledge Representation:

Knowledge Representation Issues

Issues in Knowledge Representation:

Knowledge Representation Issues

Issues in Knowledge Representation:

Knowledge Representation Issues

Issues in Knowledge Representation:

Selecting candidate knowledge structures to match a particular problem-solving situation is a hard problem:

Knowledge Representation Issues

Issues in Knowledge Representation:

Refer to specific stored links between structures to suggest new directions in which to explore.