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INTELLIGENCE: It is the capability of reasoning and taking decisions. ARTIFICIAL INTELLIGENCE: Artificial Intelligence broadly defined as concerned with the Intelligent behavior in artifacts. Artificial Intelligence have always been surrounded by controversy Question of interest raised here is,

“CAN MACHINES THINK?” Somewhat supporting and hope raising answer is that, “A virus can be called as a Machine One made of proteins”. Finally it’s got modified to, ”The study of how to make computers do things which at the Moment , people do better”.

EXPERT: An expert is a person who, because of training and experience ,is able to do things The rest of us cannot. Experts are not only proficient but also smooth and efficient in the actions they take.

EXPERT SYSTEMS: An expert system is a computer program using expert knowledge to attain high levels of performance in a narrow problem area. They are the capable programs that contained the knowledge requirements to mimic expert human performance at several tasks, including diagnosis, design and analysis.

EXPERT

Vs EXPERT SYSTEMS:

This topic is explained by dividing the differences into various headings.

1.

LIFETIME:

The human expertise is Perishable. The Artificial expertise is Permanent.

2.

PORTABILITY:

Human expertise is difficult to transfer. Artificial expertise is easy to transfer.

3.

DOCUMENTATION: Human expertise is difficult to document. Artificial expertise is easy to document.

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EXPERT PROGRAMS Vs CONVENTIONAL PROGRAMS: • •

The basic difference is that expert systems manipulate KNOWLEDGE while conventional programs manipulate DATA. The expert systems use heuristic techniques where conventional programs use algorithms.

FEATURES OF EXPERT SYSTEMS: 1.CORPUS OF KNOWLEDGE: The heart of expert system is the powerful corpus of knowledge. The accumulation and codification of knowledge is one of the most important aspects of an ES. 2.HIGH LEVEL EXPERTISE:

This feature is provided to aid in problem solving. The expertise can represent the best thinking of the top expert in the field, leading to problem solutions that are imaginative, accurate and efficient

3.PREDICTIVE MODELLING:

The system can act as an information processing theory or model of problem solving in the given domain, providing the desired answers for a given problem situation and showing how they would change for new situations.

4.TRAINING FACILITY:

This feature is provided for key personnel and important staff members. Expert systems can be designed to provide such training, since they already contain the necessary knowledge and the ability to explain their reasoning processes.

PLAYERS IN

EXPERT SYSTEM GAME:-

The main players in the expert system game are the: Expert System:

An expert system is a computer program using expert knowledge to attain high levels performance in a narrow problem area.

Domain Expert-

He is an articulate, knowledgeable person with a reputation for producing good solutions to problems in a particular field.

Knowledge Engineer- He is a human, usually with a background in computer Science and AI ,who knows how to build expert systems.

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3 Visit. www.geocities.com/chinna_chetan05/forfriends.html Expert System Building Tool-

It is the programming language used by the Knowledge engineer or programmer to build the Expert system.

The user-He is the human who uses the expert system once it is developed.

Domain expert

Toolbuilder Builds

EXPERT SYSTEM BUILDING TOOL

Extends and test

Interviews

Uses

Knowledge Engineer

Builds, refines, and tests

EXPERT SYSTEM

Uses

End-user

Adds data Clerical Staff

FRAMEWORK-The Organisation: Knowledge, mean the information a computer program needs before it can behave Intelligently .This knowledge should undergo two phases .They are:

Organising Knowledge:Many of the rules in expert systems are heuristics-rules of thumb or simplifications that effectively limit the search for solutions. Expert systems use heuristics because the tasks these systems undertake, such as finding new mineral deposits or settling a lawsuit, are typically difficult and poorly understood. An algorithmic method guarantees to produce the correct or optimal solution to a problem, while a heuristic method produces an acceptable solution to most of them. The Knowledge Base in an expert system contain, ->Facts ->Rules The “Inference Engine” contains an interpreter that decides how to apply the rules to infer new knowledge.

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REPRESENTING KNOWLEDGE: are,

The three most widely used representations used in current expert systems ->Rules ->Semantic Nets ->Frames

1. RULE: A formal way of specifying a recommendation, directive, expressed as,

“IF premise THEN conclusion”. Rule based knowledge representation centers on the use of IF condition THEN action statements. Eg:-if the patient was an insulator before 1965, Then the patient directly handeled asbestos. This sort of matching is what are called “Inference Chains”. 2. FRAME :It is a knowledge representation method that associated features with nodes Representing concepts or objects. Frame based knowledge representation uses a network of nodes connected by relations and organized into a hierarchy. Each node represents a concept that may be described attributes and values associated with the node. Nodes low in the hierarchy automatically inherits the properties of higher-level nodes. 3.SEMANTICNET: The part of the representation method consisting of a network of nodes standing for concepts or objects, connected by arcs describing the relations between the nodes.

LANGUAGES FOR EXPERT SYSTEM APPLICATIONS: The programming languages used for expert system applications and generally either Problem-oriented languages ,such as FORTRAN and PASCAL, or symbolic-manipulation languages, such as LISP and PROLOG ..

KNOWLEDGE ENGINEERING LANGUAGES: A knowledge engineering language is a sophisticated tool for developing expert systems. Knowledge engineering languages can be categorized as either Skeltel Systems or General purpose systems. Ex: The prospector has been stripped into KAS , a skeletal system. SUPPORT FACILITIES: The support facilities consist of tools for helping with programming, such as debugging aids and knowledge base editors, and tools that enhance the capabilities of the finished system, such as built-in input/output and explanation mechanisms. DEBUGGING AIDS: Most programming languages contain tracing facilities and break packages. IO FACILITIES: Different tools deal with input/output in different ways. Some provide Run time Knowledge acquisition. Ex. EMYCIN programs ask the user for needed information whenever they cant find it in the knowledge base Email: [email protected]

5 Visit. www.geocities.com/chinna_chetan05/forfriends.html EXPLANATION FACILITIES: Almost all expert systems can explain to users how they reach particular conclusions, but not all provide the same degree of software support explanation. EX:MYCIN, have a complete explanation mechanism built into the tool itself, so that any expert system written in that language can automatically access the mechanism. The most common type of explanation mechanism deals with Retrospective reasoning; it explains how the system reached a particular state. They also handle Hypothetical Reasoning, where the system explains what would have happened differently if a particular fact or rule had been different, and counter factual reasoning why an expected conclusion was not reached.

STAGES IN THE DEVOLOPMENT OF EXPERT SYSTEM TOOLS EXPERIMENTAL SYSTEMS: Created for a specific task; the devoloper seldom supports this. RESEARCH SYSTEMS: They may be extensively tested and may be supported by developer. But slow and inefficient. COMMERCIAL SYSTEMS: They polished,streamlined,well_supportive and fast.

REAL TIME EXAMPLE: EMYCIN TOOL: EMYCIN TYPE: Skeletal system FEATURES: Rule-based, Back-ward chaining, Certainty handling, Explanation IMPLEMENTATION LANGUAGE: INTERLISLP DEVELOPER: Stanford University RULE: IF the material composing the substructure is one of metals and The analysis error that is tolerable is between 5 and 30, and The non dimensional stress of the substructure is greater than 90 THEN It is definite that fatigue is one of the stress behavior in substructure ACTUAL EMYCIN RULE: PREMISE: ($AND (SAME CNTXT MATERIAL (LIST OF METALS)) (BETWEEN * CNTXT ERROR 5 30) (GREATERP * CNTXT NO-STRESS 0.9) (BETWEEN* CNTXT CYCLE 1000 1000 )) ACTION:(CONCLUDE CNTXT SS-STRESS FATIGUE TALLY 1.0)

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ELIGIBILITIES FOR AN EXPERT SYSTEM: o o o o o o o

Task does not require common sense Task require only congnitive skills Experts can articulate their methods Genuine experts exist Experts agree on solutions Task is not too difficult Task is not properly understood

STEPS IN BUILDING AN EXPERT SYSTEM IDENTIFICATION: How con important aspects in task be recognized? CONCEPTUALIZATION: What concepts need to produce a solution? FORMALISATION: How can the knowledge be formally represented? IMPLEMENTATION: What rules will embody the knowledge? TESTING: How can the rules be validated?

EXPERT SYSTEM SHELLS: In general the systems were constructed as a set of declarative representations (rules) Combined with an interpreter for those rules, it was possible to separate the interpreter From the domain-specific knowledge and thus to create a system that could be used to Construct new expert systems by adding new knowledge to the new problem domain. The resulting interpreters are called as “Shells”. Ex:-

EMYCIN is the SHELL for the famous expert system described Above - THE MYCIN.

DETAILED EXPLANATION OF AN EXPERT SYSTEM“PROSPECTOR”:-

Application Area:-

GEOLOGY

Categories Covered Under ES Applications:- INTERPRETATION DIAGNOSIS DEBUGGING

History:-Expert system work in Geology started with Prospector, a system developed by Stanford Research Centre in 1970.Prospector was designed to help Geologists locate ore deposits and accurately predict the existence of a Multi million dollar molybdenum deposit in 1980.

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Effort Taken:-> -> ->

Prospector was implemented directly in INTERLISP, a powerful but relatively low-level language as far as expert-system building tools go. A sophisticated support package was developed for PROSPECTOR that included both explanation and knowledge acquisition facilities. The system needed extensive domain knowledge.

PROSPECTOR AT WORK: Ex:-

-> -> -> ->

Let’s discuss this with an example. An exploration geologist starts by telling the program the Characteristics of a particular prospect of interest-the geological setting, structural controls, and kinds of rocks, minerals and alteration products present or suspected. The program compares these observations with models of various kinds of ore deposits, noting the similarities, differences, and missing information. The program then engages the geologist in a dialog to obtain additional relevant information and uses that information to make an assessment of the mineral potential of the prospect. Our goal is to provide the geologist with a service comparable to giving him telephone access to authorities on many kinds of ore deposits.

Rules Involved In The Above Example:IF: magnetite or pyrite in disseminated or veinlet form is present THEN: (2,-4) there is favourable mineralisation and texture for the Propylitic stage. Indications: ‘2’- ‘2’ indicate that the presence of evidence is mildly encouraging. ‘-4’-> ‘-4’ indicate that the absence of evidence is strongly discouraging.

EXPLANATION OF

EXPERT SYSTEM :- XCON

Application Area:COMMERCIAL BASIS History:

In 1980 it was developed to configure the computer systems. It takes up the Job of previously performed by technical editors, people who examine a Customer’s purchase order and determine what computer components need to be substituted to make order consistent.

XCON AT ->

-> ->

WORK:

It configures the systems at a very detailed level. For each order it determines necessary modifications, produces diagrams showing spatial and logical relationships between the hundreds of components that compromise a complete system. XCON performs at a level similar to that of an experienced technical editor, but it operates much faster. For example, although it takes the editor as long as 20 minutes to configure a system order, XCON can typically do it in less than a minute.

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BRIEF DESCRIPTION OF SOME ADVANCED EXPERT SYSTEMS: CONDITION MONITORING: The basic idea being to provide the process operators and shift engineers with a tool that on a 24-hour by 365 day basis performs healthchecks on the plant in order to: • Identify any inability of the plant to perform at the optimum efficiency level • Present and inform about the extent of the inability • Describe the reason for such an inability Thus, the Condition Monitoring System performs a task impossible for any human being. CMS is currently being developed for Nuclear Power Plants and is under configuration for many other plants. GEOMET - A LEADER IN FORMULATING SOLUTIONS TO GLOBAL INTIATIVES. GEOMET’ s meteorology staff, in conjunction with our artificial intelligence group, has designed and developed several pc _based expert systems to aid weather forecasters and planning personnel. GEOMET was an early leader in AI, developing one of the first expert system decision aids for forecasting. GEOMET has reasearched AI applications in all areas of environmental sciences, water management and flood control, hazardous waste investigations, and neural networking applications. CHEMICAL DEMILITARIZATION: Special Project’ s division supports the monitoring operations, and safety issues associated with chemical demilitarization, and the operation of demilitarization equipment and systems required to handle, store, destroy, transport, or dispose of recovered nonstockpile CWM and other toxic, hazardous or lethal substances. Their services include: • Materiological and air pollution modeling and monitoring • Personnel protective equipment selection, design, and development • Environmental health and safety support • RCRA/ hazwaste analysis PERSONAL PROTECTIVE EQUIPMENT: Personal protective equipment experts provide a full range of services to help define the specific level of protection required in any hazardous situation, then support client requirements form initial concept through final product development and delivery. PPE ensures performance through stringent testing, heat stress evaluation human comfort engineering, reliability qualification, environmental limits, and respiratory protection.

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EXPERT SYSTEMS WORK

AT

UNIVERSITIES:

• The main fields of interest for expert systems in universities are human problem solving, developing and applying information processing techniques to model human cognition and memory. •

Each rule would say, “If I recognize some situation S in short-memory, Then I take some action A”.

• The process of rule-evocation and memory modification to model human problem solving and called the resulting system a “Production System”.

EXPERT SYSTEMS WORK AT RESEARCH ORGANISATIONS: • The research organizations engaged in expert system work come in a variety of types ranging from experienced leaders in AI to bold newcomers. • Some are large corporations with an AI division or group. Others are small companies devoted almost exclusively to AI and expert system applications.

EXAMPLES SYSTEMS:

OF HIGH PERFORMANCE

EXPERT

IN RESEARCH FIELD:• The SYNCHEM2 expert system synthesizes complex organic molecules without assistance or guidance from a chemist. The system uses knowledge about chemical reactions to generate a plan for creating the target molecule from basic building block molecules. • The DENDRAL expert system infers the molecular structure of unknown compounds from mass spectral and nuclear magnetic response data. • The MACSYMA expert system performs symbolic manipulation of algebraic expressions, assisting the user with problems involving limit calculations, symbolic integration, solution of equations, canonical simplification, and pattern matching. IN BUSINESS:• YES/MVS, developed by IBM ,helps the computer operator monitor and control the MVS. • DELTA was developed to help maintaining personnel diagonise and repair malfunctions in diesel electric locomotives.

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WHAT’S

ACE provides troubleshooting and dioagonistic reports for telephone cable

NEXT FOR

EXPERT SYSTEMS?

Advances in computer hardware have contributed significantly to the expansion of expert systems. EXPERT SYSTEMS……………………….. INTELLIGENT SYSTEMS: Computer hardware advances have made possible “integrated expert Systems”, that is, expert systems embedded in microprocessor chips to form an Integrated hardware/software package. These integrated experts systems can be embedded in a piece of Equipment, such as complex electronic gear, to form what we will call an “intelligent System”. HIERARCHIAL INTELLIGENT SYSTEMS: The intelligent system configuration will be particularly useful when the equipment to be monitored forms a hierarchy of physical units arranged in some Network structure. • An intelligent system has already been developed and put into commercial use. • The SPE expert system runs on a microprocessor . • This expert system interpretes waveforms from destinometer to determine which of several diseases a patient might have.

UPCOMING APPLICATION AREA: EXPERT SYSTEM FOR ‘ THE LAW’: Expert systems are beginning to be noticed by the legal profession. 4 important types of applications for expert systems in law exists. They are: 1. Document Generation

:

Produces legal documents such as wills, contracts, draft legislation by selecting or composing appropriate pieces of text and organizing them into document form.

2. Interpretation and Prediction

:

Interprets the law in the context of a particular Question or problem, anticipates the legal consequences of proposed actions and predicts the effects of changes in legislation.

3. Scheduling and Monitoring

:

Schedules attorneys activities and periodically inspects legal data bases and knowledge bases for changes in the law that could affect clients and active cases.

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:

COMMON PITFALLS IN IMPLEMENTATION:

EXPERT SYSTEM

PITFALL1

:

The expert system development effort is addressing a problem so difficult that it can’t be solved within the constraints set by the available resources.

PITFALL2

:

The problem that the expert system is designed to solve will not significantly alleviate the difficulty that motivated the development effort.

PITFALL3

:

The problem that the expert system addresses is so general or complex that an excessive number of rules and data base objects are needed to describe the expertise adequately.

LIMITATIONS • • • • •

Organizes case information, estimates case value, and suggests for negotiation and case disposition.

Expert Expert Expert Expert Expert

systems systems systems systems systems

OF are are are are are

EXPERT not not not not not

SYSTEMS:-

good at representing Temporal Knowledge. good at representing Spatial Knowledge good at performing commonsense. good at recognizing their ability. good at handling the inconsistent knowledge.

CONCLUSION : Human brain undergoes an everlasting search for something innovative and so is the case……… ES are the invention that was fuelled by the idea of making machines intelligent. There are 2 basic motivations that lie behind all scientific and Technological inventions…… The man’s inherent desire to function with least effort and of strong desire to be the Master. Undoubtedly we can expect a lot from these in future to say truly there’s no limit for what it can do. Even the fictious thought of replacing the entire political infrastructure of a nation by ES can be made possible by adding to it all the human elements such as humanity, future awareness etc.. , thereby getting rid of the political Evils such as corruption, conspiracies by not entering them into its knowledge base.

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