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					      R.S.P.KIRAN PAPER PRESENTATION

                     ON

ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS

SRI KAVITHA ENGINEERING COLLEGE KAREPALLY



                R.S.P.KIRAN

                HNO:10_4_43

             MAMILLAGUDUM

                KHAMMAM

           EMAIL: gkrisv@yahoo.com
Abstract:

                                           Artificial intelligence is a term that encompasses many

definitions and most experts agree that Ai is concerned with two basic ideas. First, it involves

studying the thought processes of humans, secondly it deals with representing this processes via

machines.

                                  Ai definition also follows the behavior by machine that ,if

performed by a human being, would be called intelligence. A thought provoking definition is

provided by “Rich and knight” that is artificial intelligence is a study of how to make computers

do things at which, at the movement people are better.

                        The term intelligence behavior involves

                            1   Learning or understanding from experience.

                            2   Making sense out of ambiguous contradictory messages

                            3   Responding quickly and successfully to new situation.

                            4   Using reasoning in solving problems and directing conduct

                                effectively.

                            5   Applying knowledge to manipulate the environment

                        Thinking and reasoning.

                        AI method involve some kind of search mechanism that focus on most

                        promising areas.

   1 Inferencing: artificial intelligence involves an attempt by machines to exhibit reasoning

       capability. This reasoning consists of inferencing from facts and rules using heuristics or

       other search approaches. Artificial intelligence is unique in that it makes inferences by
       using a pattern matching approaches.

Pattern matching: the following of AI on pattern matching techniques artificial intelligence

works with pattern matching methods such as, methods that attempt to describe objects events, or

processes in terms of their qualitative features and logical computational relationships. Expert

systems,robotics ,neural networks,Natural language processing, Speech understanding, Fuzzy

logic,Genetic algorithms ,Intelligent tutors.

                                   Also involve fields such as game playing, computer vision,

 automatic programming, machine learning. Expert system can be viewed as two environments

 consultation environment and development. That development is used by an expert system

 builders to build the components and put knowledge into the knowledge base. The consultation

 environment is used by an non expert to take advise and expert knowledge.

                                                                    The three major parts that

 appear in expert systems are          knowledgebase, inference engine and user interface. It also

 contains additional parts such as

                                   1    Knowledge acquisition subsystem

                                   2    Black board (work space)

                                   3    Explanation sub system

                                   4    Knowledge refining system

                                   5    Enter users
   2 Introduction:

   Artificial intelligence v/s Natural intelligence:

   1 AI is more permanent: natural intelligence is perishable from a commercial stand point in

       that workers can change their place of employment or forget information however, AI is

       permanent as long as computer systems and programs remain unchanged.

   2 AI offers involves ease of duplication and dissemination:

   3 AI can be less expensive than natural intelligence:

   4 AI can documented: Decisions made by computer can easily documented by tracing the

       activities of the system. Natural intelligence is difficult to document.

   5 AI, being a computer technology, is consistent and through. Natural intelligence is erratic

       because people are erratic as they don’t perform consistently.

There are wide range of application of AI. They are

Expert systems,robotics ,neural networks,Natural language processing, Speech understanding,

Fuzzy logic,Genetic algorithms ,Intelligent tutors.Also involve fields such as game playing,

computer vision, automatic programming, machine learning.

   Basic concept of expert system:

                                                          The basic concept of expert system

   involve expertise, experts, transferring expertise, inferencing rule and explanation capability

   this concepts play a major role in the aggregate development of expert systems.

       1   Expertise: Expertise is the extensive, task specifying knowledge acquired from

           training reading and experience it includes the following

                     Theories about the problem area.

                     Metaknowledge
                        Facts about the problem area

                        Rules and procedure regarding the general problem and its situation.

                         These enable experts to make better and faster decision than non experts in

               solving complex problems. Expertise is usually associated with high degree of

               intelligence but it is not always associated smartest person expert knowledge is

               well stored, organized and quickly retrievable from an expert, expertise is usually

               with vast domain of knowledge. Expertise makes people to learn from their

               past success and failures.

Experts: It is difficult to define who an expert is because we can actually talk about degree or

levels of expertise.                          Nevertheless, it has been said that non experts out

number established experts in many fields by a ratio of 100:1. expert in the top tenth in any given

area are believed to perform three times as well as a average expert and thirty times as well as

those in lowest tenth.

 Human expertise includes a consolation of a behavior that involves

                                     Recognizing and formulating the problem

                                     Solving the problem quickly and correctly

                                     Learning from experience

                                     Reconstructing knowledge

                                     Break rules if necessary

                                    Transferring expertise: The objective of an expert system is to

 transfer expertise from an expert to a computer system and then to other humans. This involves

 four activities they are knowledge acquisition, knowledge representation, knowledge

 inferencing, knowledge transferring to the users.
                                 STRUCTURE OF EXPERT SYSTEM

                                 Expert system can be viewed as two environments consultation

environment and development. That development is used by an expert system builders to build

the components and put knowledge into the knowledge base. The consultation environment is

used by an non expert to take advise and expert knowledge.

                                                                The three major parts that

appear in expert systems are                            knowledgebase, inference engine and

user interface. It also contains additional parts such as

                                 6   Knowledge acquisition subsystem
                                  7   Black board (work space)

                                  8   Explanation sub system

                                  9   Knowledge refining system

                                  10 Enter users



Knowledge acquisition sub system: This is the accumulation, transfer and transformation of

problem solving expertise from experts or documented knowledge sources to a computer

programs for constructing and expanding the knowledge base. Acquiring knowledge from a

expert is a complex task that often creates a bottle neck in expert system construction. typically

the knowledge engineer helps the expert system structure the problem area by interpreting and

integrating human answers to questions, drawing analysis, posing counter examples

 Inference engine: The brain of the expert system , and also known as the rule interpreter. This

 is the component that provide a methodology for reasoning about the knowledge base and

 formulating conclusions, developing the agenda that organizes and controls the steps taken to

 solve problems when ever required.

 User interface: Expert system contains language processor for friendly, problem oriented

 communication between the user and computer. This communication can be best be carried out

 in a natural language. Some times it is supplemented by menus, electronic forms and graphics.

 Black Board: Is an area of working memory set a side as a data base for the description of the

 current problem as specified by the input data three decision can be recorded on black board

 they are a plan, a solution, an agenda.

  Explanation sub system : The explanation sub system interactively answers questions such as

                                   why was certain question asked by the expert How
 was the conclusion reached.

                                   why was a certain alternative rejected.

                                   What is the plant reach solution



 Knowledge refining system: This system analyze its own knowledge and its use, learn from it

 and improve on it for future consultation. This could lead to improvement that result in more

 accurate knowledge base and more effective reasoning.

 The user: The user of an expert system id usually an non expert who needs adivce and training.

 The user is considered as part of expert system while other people are involved in its

 construction.

                                  How an expert system work:

                                               ES construction and use consist of three major

 activities development, consultation, improvement .

                                  1   Development : The development of an expert system

 involves the construction of a problem specific knowledge base by acquiring      knowledge

 from knowledge base by acquiring knowledge from experts or documented sources the

 knowledge is then separated into declarative and procedural then it also includes construction

 of a interface engine, a blackboard, an explanation facility and any other required software,

 such as interfaces.

ES shell is a tool of an used to expedite development.

 Consultation: Once the system as been developed and validated it can be deployed to users the

 ES conducts a bidirectional dialogue with a user asking for facts about a specific incident.

 While answer is being received the Es attempts to reach the conclusion this effort is made by
inference engine , which chooses search techniques to be used to determine how the rules in

the knowledge base are to be applied to each other. The user can ask for explanations. The

quality of the interface capability is determined by the quality and completeness of the rules by

the knowledge representation used, by the power of the inference engine.

Improvement: The expert systems are improved several times through a process called rapid

prototyping. The computer keeps asking questions asked earlier and improve the knowledge

base frequently.




PROBLEM AREAS ADDRESSED BY EXPERT SYSTEM

Expert system address a wide range of problem areas such as

                                i. Interpretation systems infer situation descriptions from

observations. This category

                                Includes speech understanding image analysis, signal

interpretation and many kinds of intelligent analysis. An interpretation system explains

observed data by assigning them symbolic meanings describing the situation

                                ii. Prediction system includes weather forecasting

demographic predictions, economic forecasting, crop estimation, military marketing, and

financial forecasting.

                                iii. Designing system develop configuration of the objects that

satisfies the constrains of the design problems such problem include circuit layout, and plant

layout. This constructed descriptions of objects with various relationships with one another and
 verify that these configurations conform to stated constraints.

                                 iv. Debugging systems relay on planning, design, and

 prediction capabilities for creating specification to correct a diagnosed problem

                                 v. Control systems adaptively govern the over all behavior of

 the system. To do this, the control system must repeatedly interpret the current situation,

 predict the future, anticipate the cause of problem and formulate a remedial plan.




BENEFITS OF EXPERT SYSTEMS

                                 Thousands of ES are in use today almost in every industry and

 in every functional area. The major ES benefits are discussed

 Increase output and productivity Flexibility

 Easier equipment operation

 Elimination of the need for expensive equipment

 Knowledge transferred to remote location

 Availability to solve complex problems

 Ability to work with incomplete or uncertain information

 Operation in hazardous environment

 Improved decision quality

 Enhancement of other information systems

 Decrease decision making time

 Increase process and product quality

 Reduce down time

 Capture of scare expertise
EXPERT SYSTEMS SUCCESS FACTOR

                             1   The level of knowledge must be sufficiently high.

                             2   The problem domain should be narrow

                             3   Knowledge base should be improved frequently

                             4   Management support must be cultivated

                             5   Es shell must be of high quality and naturally store and

 manipulate the knowledge.

                             6   Expertise must be available from atleast one cooperative

 expert

                             7   The user interface must be friendly for novice user

				
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posted:7/17/2011
language:English
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