artificial intelligence: chapter 4 introduction to knowledge base systems

8/18/2019 Artificial Intelligence: Chapter 4 Introduction to Knowledge Base Systems

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Artificial Intelligence

Introduction to Knowledge Base SystemsDr. Zeeshan Bhatti

BSSW-PIV

Chapter 4

Institute of Information and Communication TechnologyUniversity of Sindh, Jamshoro By: D r. Zeeshan Bhat ti 1DR. ZEESHAN BHATTI 1


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KBSS & KNOWLEDGE

What is a knowledge-based system? A system which is built around a knowledge base. i.e. a collection of

knowledge, taken from a human, and stored in such a way that the systemcan reason with it.

What is knowledge? Knowledge is the sort of information that people use to solve problems.

DR. ZEESHAN BHATTI 2


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KNOWLEDGE

Knowledge includes: facts, concepts, procedures, models, heuristics, examples.

Knowledge may be: specific or general

exact or fuzzy

procedural or declarative



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A KNOWLEDGE-BASED AGENT

A knowledge-based agent includes a knowledge base and an inference system.

A knowledge base is a set of representations of facts of the world.

Each individual representation is called a sentence.

The sentences are expressed in a knowledge representation language.

The agent operates as follows:

1. It TELLs the knowledge base what it perceives.

2. It ASKs the knowledge base what action it should perform.3. It performs the chosen action.

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ARCHITECTURE OF AKNOWLEDGE-BASED AGENT

Knowledge Level.

The most abstract level: describe agent by saying what it knows.

Example: A taxi agent might know that the Golden Gate Bridge connects San Francisco withthe Marin County.

Logical Level.

The level at which the knowledge is encoded into sentences.

Example: Links(GoldenGateBridge, SanFrancisco, MarinCounty).

Implementation Level.

The physical representation of the sentences in the logical level. Example: ‘(links goldengatebridge sanfrancisco marincounty)

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EXPERT SYSTEMS

What is an expert system? A particular kind of knowledge-based system

One in which the knowledge, stored in the knowledge base, has been takenfrom an expert in some particular field.

Therefore, an expert system can, to a certain extent, actas a substitute for the expert from whom the knowledgewas taken.



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ARTIFICIAL INTELLIGENCE

What is Artificial Intelligence?

Artificial Intelligence (AI) is concerned with exploring suchaspects of human (and other animal) mental activity as: understanding creativity

perception problem-solving

consciousness using language

intelligence

by simulating them using computers.



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It is therefore closely connected with such socialsciences as: psychology

linguistics

philosophy



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APPLIED ARTIFICIAL INTELLIGENCE

What is applied AI?

Applied AI is concerned with producing software which is“intelligent”

It is intelligent in that it is based on what we know abouthuman reasoning and other mental abilities

We are therefore talking about a branch of advancedcomputing - computer technology - rather than socialscience



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KNOWLEDGE ENGINEERING

The term “knowledge engineering” is often used

to mean the process of designing

building

installing

an expert system or other knowledge-based

system.

Some authors use the term to mean just theknowledge acquisition phase.



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EXPERTS

An expert is an experienced practitioner inhis/her particular field. More than that, he/she is

a highly effective problem-solver and decision-taker in that field.

Experts have three qualities: They make good decisions

They make those decisions quickly

They are able to cope with a wide range of problems.



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EXPERTS AND EXPERT SYSTEMS

Note that: The task that an expert system performs will generally be regarded

as difficult. An expert system almost always operates in a rather narrow field ofknowledge. The field of knowledge is called the knowledge domainof the system.

There are many fields where expert systems can usefully be built.

There are many fields where they can’t.



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EXPERTS AND EXPERT SYSTEMS

Note also that an expert can usually explain

and justify

his/her decisions.



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REASONS FOR BUILDING AN E.S.

One might build an expert system for any or allof the following reasons: To archive an expert’s knowledge, to insure against the day whenhe/she leaves, or retires, or dies.

To disseminate his/her knowledge, so that it is available in more(possibly many more) places than the location of the expert.

To ensure uniformity of advice/decisions.

As a basis for training other specialists.



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REPRESENTATION, REASONING, AND LOGIC

The object of knowledge representation is to express knowledge in acomputer-tractable form, so that agents can perform well.

A knowledge representation language is defined by:

its syntax, which defines all possible sequences of symbolsthat constitute sentences of the language.

Examples: Sentences in a book, bit patterns in computer memory.

its semantics, which determines the facts in the world to whichthe sentences refer.

Each sentence makes a claim about the world.

An agent is said to believe a sentence about the world.

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THE CONNECTION BETWEEN

SENTENCES AND FACTS

Semantics maps sentences in logic to facts in the world.

The property of one fact following from another is mirrored

by the property of one sentence being entailed by another.

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SOUNDNESS AND COMPLETENESS

A sound inference method derives only entailed sentences.

Analogous to the property of completeness in search, acomplete inference method can derive any sentence that isentailed.

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LOGIC AS A KR LANGUAGE

Propositional Logic

First Order

Higher Order

Modal

Fuzzy

Logic

Multi-valuedLogic

Probabilistic

Logic

Temporal Non-monotonicLogic

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NO INDEPENDENT ACCESS TO THE WORLD

• The reasoning agent often gets its knowledge about the facts of

the world as a sequence of logical sentences and must draw

conclusions only from them without independent access to the

world.

• Thus it is very important that the agent’s reasoning is sound!

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SUMMARY

Intelligent agents need knowledge about the world for making gooddecisions.

The knowledge of an agent is stored in a knowledge base in the form ofsentences in a knowledge representation language.

A knowledge-based agent needs a knowledge base and an inferencemechanism. It operates by storing sentences in its knowledge base,inferring new sentences with the inference mechanism, and using them todeduce which actions to take.

A representation language is defined by its syntax and semantics, which

specify the structure of sentences and how they relate to the facts of theworld.

The interpretation of a sentence is the fact to which it refers. If this fact ispart of the actual world, then the sentence is true.

DR. ZEESHAN BHATTI

artificial intelligence: chapter 4 introduction to knowledge base systems

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