Expert system .

• expert system

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Expert system

1 In Artificial Intelligence, an expert system is a computer system that emulates the decision-

making ability of a human expert. Expert systems are designed to solve complex

problems by reasoning about knowledge, represented primarily as IF-THEN rules rather than through conventional procedural code. The first expert systems were created in the

1970s and then proliferated in the 1980s. Expert systems were among the first truly

successful forms of AI software.


Expert system

1 An expert system has a unique architecture, different from traditional computer

programming. It is divided into two parts, one fixed, independent of the expert system: the

inference engine, and one variable: the knowledge base. The knowledge base

represents facts about the world and rules. The inference engine applies the rules to the known facts to deduce new facts. Inference engines can also include explanation and

debugging capabilities.


Expert system - History

1 Hayes-Roth expressed the key insight of early expert systems to be that

intelligent systems derive their power from the knowledge they

possess rather than from the specific formalisms and inference schemes

they use



1 Expert systems were introduced by the Stanford Heuristic Programming Project

led by Edward Feigenbaum who is sometimes referred to as the "father of

expert systems". The Stanford researchers tried to identify domains

where expertise was highly valued and complex such as diagnosing infectious

diseases (Mycin) and identifying unknown organic molecules (Dendral)



1 In addition to Feigenbaum key early contributors were Bruce Buchanan,

Edward Shortliffe, Randall Davis, William vanMelle, and Carli Scott.

Expert systems were among the first truly successful forms of AI software.



1 The advantage of expert system shells was that they were somewhat easier for non-

programmers to use



1 In the 1980s, expert systems proliferated. Universities offered

expert system courses and two thirds of the Fortune 1000 companies applied the technology in daily business activities. Interest was

international with the Fifth Generation Computer Systems project in Japan and increased

research funding in Europe.https://store.theartofservice.com/the-expert-system-toolkit.html


1 Up until that point the primary development environment for expert

systems had been high end Lisp machines from Symbolics and Texas

Instruments



1 Many of the leading major business application suite vendors such as SAP, Siebel, and Oracle integrated

expert system capabilities into their suite of products as a way of

specifying business logic


Expert system - Software architecture

1 An expert system is an example of a knowledge-based system. Expert

systems were the first commercial systems to use a knowledge-based architecture. A knowledge-based

system is essentially composed of two sub-systems: the knowledge base and the inference engine.



1 In later expert systems developed with commercial shells the

knowledge base took on more structure and utilized concepts from

object-oriented programming



1 One of the early innovations of expert systems shells was to

integrate inference engines with a user interface



1 As Expert Systems evolved many new techniques were incorporated

into various types of inference engines. Some of the most important

of these were:



1 Although they were not highly used in expert systems classifiers are very

powerful for unstructured volatile domains and are a key technology for the Internet and the emerging

Semantic Web.


Expert system - Advantages

1 With an expert system the goal was to specify the rules in a format that was intuitive and easily understood,

reviewed, and even edited by domain experts rather than IT experts



1 With an expert system shell it was possible to enter a few rules and

have a prototype developed in days rather than the months or year

typically associated with complex IT projects.



1 In addition as expert systems moved from prototypes in the lab to

deployment in the business world issues of integration and

maintenance became far more critical


Expert system - Disadvantages

1 These problems with expert systems were essentially the same problems

as any other large system: integration, access to large

databases, and performance.


Expert system - Disadvantages

1 As a result a great deal of effort in the later stages of expert system tool

development were focused on integration with legacy environments

such as COBOL, integration with large database systems, and porting

to more standard platforms


Expert system - Applications

1 Also, while these categories provide an intuitive framework for describing

the space of expert systems applications, they are not rigid

categories and in some cases an application may show characteristics

of more than one category.



1 For the most part this category or expert systems was not all that successful



1 Dendral was a tool to study hypothesis formation in the identification of organic molecules. The general problem it solved

—designing a solution given a set of constraints—was one of the most

successful areas for early expert systems applied to business domains such as

sales people configuring Dec Vax computers and mortgage loan

application development.



1 SMH.PAL is an expert system for the assessment of students with multiple

disabilities.


Expert systems

1 In Artificial Intelligence, an 'expert system' is a computer system that emulates the

decision-making ability of a human expert. Expert systems are designed to solve complex

problems by reasoning about knowledge, represented primarily as IF-THEN rules rather

than through conventional procedural code. The first expert systems were created in the 1970s

and then proliferated in the 1980s. Expert systems were among the first truly successful

forms of Artificial Intelligence|AI software.


Expert systems

1 Inference engines can also include explanation and debugging

capabilities., School of Science Education, Expert system: a catalyst

in educational development in Nigeria: Knowledge-based systems

collect the small fragments of human know-how into a knowledge-base which is used to reason through a

problem, using the knowledge that is appropriated


Expert systems - History

1 Expert systems were introduced by the Stanford Heuristic Programming Project led by Edward Feigenbaum

who is sometimes referred to as the father of expert systems. The

Stanford researchers tried to identify domains where expertise was highly

valued and complex such as diagnosing infectious diseases Mycin|

(Mycin) and identifying unknown organic molecules Dendral|(Dendral)



1 Stubblefield, Benjamin/Cummings Publishers, Rule Based Expert

System Shell: example of code using the Prolog rule based expert system shell, Université de Liège, Belgique:

PROLOG, the first declarative language



1 In the 1980s, expert systems proliferated. Universities offered

expert system courses and two thirds of the Fortune 1000 companies applied the technology in daily

business activities.Durkin, J. Expert Systems: Catalog of Applications.

Intelligent Computer Systems, Inc., Akron, OH, 1993. Interest was

international with the Fifth Generation Computer Systems project in Japan and increased

research funding in Europe.



1 Up until that point the primary development environment for expert

systems had been high end Lisp machines from Xerox, Symbolics Inc.|

Symbolics and Texas Instruments



1 Many of the leading major business application suite vendors such as

SAP (software)|SAP, Siebel Systems|Siebel, and Oracle Corporation|Oracle integrated expert system

capabilities into their suite of products as a way of specifying

business logic


AI Winter - The fall of expert systems

1 Expert systems proved useful, but only in a few

special contexts


AI Winter - The fall of expert systems

1 The few remaining expert system|expert system shell companies were eventually forced to downsize and

search for new markets and software paradigms, like case based reasoning

or universal database access


History of AI - The neats: logic, Prolog and expert systems

1 Prolog uses a subset of logic (Horn clauses, closely related to rules and production system|production rules) that permit tractable computation.

Rules would continue to be influential, providing a foundation for

Edward Feigenbaum's expert systems and the continuing work by Allen Newell and Herbert A. Simon that would lead to Soar (cognitive

architecture)|Soar and their Unified Theory of Cognition|unified theories

of cognition.


History of AI - The rise of expert systems

1 An expert system is a program that answers questions or solves

problems about a specific domain of knowledge, using logical production system|rules that are derived from

the knowledge of experts. The earliest examples were developed by

Edward Feigenbaum and his students. Dendral, begun in 1965,

identified compounds from spectrometer readings. MYCIN, developed in 1972, diagnosed infectious blood diseases. They

demonstrated the feasibility of the approach. (Dendral), ,



1 Expert systems restricted themselves to a small domain of specific knowledge (thus avoiding the

commonsense knowledge problem) and their simple design made it

relatively easy for programs to be built and then modified once they

were in place. All in all, the programs proved to be useful: something that

AI had not been able to achieve up to this point. and



1 Corporations around the world began to develop and deploy expert

systems and by 1985 they were spending over a billion dollars on AI, most of it to in-house AI departments


Software agent - Distinguishing agents from expert systems

1 * Expert systems are not coupled to their environment;


R1 (expert system)

1 The 'R1' (later called 'XCON', for e'X'pert 'CON'figurer) program was a production-rule-based system written

in OPS5 by John P. McDermott of Carnegie Mellon University|CMU in 1978 to assist in the ordering of

Digital Equipment Corporation|DEC's VAX computer systems by

automatically selecting the computer system components based on the

customer's requirements. The development of XCON followed two

previous unsuccessful efforts to write an expert system for this task, in

FORTRAN and BASIC).


R1 (expert system)

1 XCON's success led DEC to Rewrite (programming)|rewrite XCON as 'XSEL'- a

version of XCON intended for use by DEC's salesforce to aid a customer in properly

configuring their VAX (so they wouldn't, say, choose a computer too large to fit through their doorway or choose too few cabinets

for the components to fit in). Location problems and configuration were handled

by yet another expert system, 'XSITE'.


Expert systems

1 Expert systems are designed to solve complex problems by automated

reasoning|reasoning about knowledge, represented primarily as

Rule-based system|if–then rules rather than through conventional procedural code. The first expert

systems were created in the 1970s and then proliferated in the 1980s.

Expert systems were among the first truly successful forms of Artificial

Intelligence|AI software.


Expert systems

1 Inference engines can also include explanation and debugging capabilities.

[http://www.hrmars.com/admin/pics/261.pdf Nwigbo Stella and Agbo Okechuku Chuks],

School of Science Education, Expert system: a catalyst in educational development in

Nigeria: Knowledge-based systems collect the small fragments of human know-how into a knowledge-base which is used to

reason through a problem, using the knowledge that is appropriated



1 Edward Feigenbaum in a 1977 paper said that the key insight of early

expert systems was that intelligent systems derive their power from the knowledge they possess rather than

from the specific formalisms and inference schemes they use (as

paraphrased by Hayes-Roth, et al.) Although, in retrospect, this seems a rather straightforward insight, it was a significant step forward at the time



1 Expert systems were introduced by the Stanford Heuristic Programming Project led by Feigenbaum, who is

sometimes referred to as the father of expert systems. The Stanford

researchers tried to identify domains where expertise was highly valued and complex, such as diagnosing infectious diseases (Mycin) and

identifying unknown organic molecules (Dendral).



1 In addition to Feigenbaum key early contributors were Edward Shortliffe, Bruce Buchanan, and Randall Davis. Expert systems were among the first

truly successful forms of Artificial Intelligence|AI software.



1 Stubblefield, Benjamin/Cummings Publishers, Rule Based Expert

System Shell: example of code using the Prolog rule based expert system

shell[http://promethee.philo.ulg.ac.be/engdep1/download/prolog/htm_docs/

prolog.htm A



1 Many of the leading major business application suite vendors such as

SAP (software)|SAP, Siebel Systems|Siebel, and Oracle Corporation|Oracle integrated expert system

capabilities into their suite of products as a way of specifying

business logic


Expert systems for mortgages

1 They also see in the application of expert systems a possibility for

standardized, efficient handling of mortgage loans, and appreciate that

for the acceptance of mortgages there are hard and fast rules which do not always exist with other types

of loans.



1 The expert system corrects this

failure”.



1 The expert system also capitalizes on regulatory possibilities. In France, the government subsidizes one type of loan which is available only on low-

cost properties (the HLM) and to lower income families. Known as

frets Conventionnes, these carry a rate of interest lower than the rate

on the ordinary property loan from a bank. The difficulty is that granting

them is subject to numerous regulations, concerning both:



1 Expert system for mortgages takes care of these by providing branch employees with tools permitting them to process an application

correctly, even if a bank employee does not have an exact knowledge of

the screening procedure.


Expert systems for mortgages - Goals and Objectives

1 The expert system neither refuses nor grants loans, but it:



1 * means and the security to be obtained from him.Expert systems in

banking: a guide for senior managers./Dimitris N.Chorafas and

Heinrich Steinmann. p. 222-225.



1 The expert system provides the branch with a significant amount of

assistance simply by producing correct applications for a loan. In

many cases the client had to choose between different types of loans, and

it was planned that expert system should enable bank employees to advise clients on the type of loan which best matched their needs.

This, too, has been done and as such contributes to the bank employees'

training.



1 The main tasks of expert system for

mortgages focused on:



1 Simple expert systems constitute the first phase of a loan application for

mortgage purposes. After a prototype is made, the construct

should be presented to expert loan officers who, working together with

the knowledge engineer(s) will refine the first model. But if there is no first

try which is simple and understandable, there will not be

complex real-life solutions afterwards.



1 Whether simple or sophisticated, an expert system for mortgages should

be provided with explanation facilities that show how it reaches its decisions and hence its advice. The confidence of the loan officer in the AI construct will be increased when this is done in a convincing manner.


Expert systems for mortgages - Application of expert systems for mortgages

1 Through the Mavent Compliance Console (MC2), the front-end

interface to the Mavent Expert System, Fannie Mae review loans for compliance with its policies on the Truth in Lending Act (TILA), federal

and state high-cost lending laws, and the points-and-fees test as outlined

in the Fannie Mae Selling and Servicing Guide.



1 Expert systems for mortgages can be used not only in mortgage banking,

but also in law. There are some expert system that was developed to assist attorneys and paralegals in the closing process for commercial real

estate mortgage loans.



1 An Expert System for Legal

Consultation


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