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What are the Prerequisites of the Artificial Intelligence?

The Artificial Intelligence involves the ability to be intelligent artificially and must possess the ability to come out with the human like responses and for the achievement of all these features, the computer must have the following requisite features –

1. Under – stand what is the ‘common sense’.
2. Under – stand the ‘facts’ and the various relationships existing between these facts.
3. Must be able to manipulate the data based on the quality.
4. Must be able to tackle the various exceptions that may creep in.
5. Should be able to deal with the discontinuity.
6. Must be able to inter – face with the humans in a ‘free – format’ fashion.
7. Should be able to tackle the various new situations that may arise and such critical situations should be handled based on the previous learning.

What are the applications of the Artificial Intelligence?
1. Financial Management
2. Manufacturing the planning and the scheduling
3. Factory Management
4. Project Management
5. Port – folio Management
6. Sales services
7. Field services
8. Geology
9. Distribution services
10. Diagnosis
11. Trouble shooting
12. Currency / Interest rates SWAP’s
13. Asset liability Management
14. Reading / interpreting financials
15. Criminology

Differentiate between Natural Intelligence and the Artificial Intelligence

S.NO. Features Natural Intelligence Artificial Intelligence
1. Sensor using capability High Low
2. Creative and imaginative ability High Low
3. Ability to learn from the past experiences High Low
4. Adaptive ability High Low
5. Ability to afford the cost of the acquiring intelligence High Low
6. Ability to use the information source varieties High High
7. Ability of acquiring the high amount of the external information High High
8. Ability of making the complex calculations Low High
9. Information transferring ability Low High
10. Ability to make a series of the different types of the calculations at a good high speed and all this in a very accurate way Low High

What is Artificial Intelligence?

Introduction
Artificial Intelligence can be defined as an area having over half a century of the history. First of all in the late 1940’s, the emergence of the computers took place and it was during this phase only that the Artificial Intelligence began in the earnest.

These machines have the ability to store huge amount of the data and after this step these machines process it into the information at a very high speed. Although the Artificial Intelligence was born in the 1940’s but it did not receive a great response from the various users at that particular time. It was only in the 1980’s that the Artificial Intelligence received the popular economic and the managerial acclaim. All along during this period, a large amount of the transition took place in the concept of the Artificial Intelligence and one of the main transitions included the transition from a primary research area to the potential commercial applications.

After this period of the major transitions only, the Artificial Intelligence was accepted as an emerging technology and got a very hot response from the different types of the users using it. The major reason of its acceptance was the fact that the Artificial Intelligence does – not replace people but in fact the Artificial Intelligence liberate the experts from solving the common and the simple types of the problems, hence in – turn leaving the experts for solving the various complex problems.

One of the major advantages of the Artificial Intelligence is that it helps to avoid making the mistakes and also helps in responding very quickly to any type of the problem that may arise.

Meaning and the Definition
George Luger and William Stabblefied defined Artificial Intelligence as “a branch of the computer science that is mainly concerned with the automation of the intelligent behavior”.

Dan Patterson defined Artificial Intelligence as “a branch of the computer science concerned with the study and the creation of the computer systems that exhibit some form of the intelligence: systems that learn the new concepts and the tasks, systems that can reason and also draw the useful conclusions about the world around us, systems that can under – stand the various natural languages and perceive and comprehend a visual scene and the systems that perform the other types of the feats that essentially require the human types of the intelligence”.

Artificial Intelligence can be under – stood as the technology playing a very major part in the application of the computers to the areas or the fields, which requires the basic knowledge, the perception, the reasoning, the understanding and the cognitive abilities. By having all this, it really becomes possible to distinguish the human behavior from the machines like the computers etc. Artificial Intelligence actually is the science and the engineering involving the making of the intelligent machines and one major point to be remembered here is that the Artificial Intelligence is related a great deal to the similar task of making use of the computers in order to under – stand the human intelligence. Human intelligence is also referred to as the natural intelligence and the below explained comparison between the Natural Intelligence and the Artificial Intelligence helps a great deal in under – standing the concept of both the Artificial Intelligence and the Natural Intelligence and the basic differences that occur between them.

What are the Limitations of the Expert Systems?

Limitations of the Expert Systems

1. The concept of the Expert Systems mainly involves a very narrow range of the codified domain.
2. The Expert Systems are not generally adopted at managing the highly sophisticated sensory inputs.
3. The Expert Systems mainly function in the domain of the extracted, cognitive, logical thinking process.
4. The different types of the multi – dimensional problems that are faced by the various users while performing the various activities, cannot be efficiently tackled by the Expert Systems.
5. Some of the typical Expert Systems at times are not able to make available common sense knowledge and the broad – ranging contextual information.
6. Very narrow range of the knowledge is incorporated in the Expert Systems.
7. The Expert Systems do – not respond well to the various situations out – side their range of the expertise.
8. The Expert Systems remain what they are – the machine experts.
9. The human self – awareness is lacking in the Expert Systems.
10. The various Expert Systems lack the much needed self – analysis tools.
11. The Expert Systems are non – self referral systems.
12. In case of the Expert Systems, no introspection is possible.
13. The Expert Systems have the ability of performing only with – in a specific, logical – oriented realm of the expertise.

What are the Applications of Expert Systems?

Following are the applications of Expert Systems:-

1. Make computer programming very easier in the nature.
2. Make computer programming effective in the working.
3. Transforms the computing by moving the programming technologies beyond the numerical programming into a realm of the logical and the symbolic programming.
4. Helps to solve the different types of the problems practically of every field and every discipline.
5. Play a very critical role in the different stages of the problem – solving process.
6. Have a variety of the complex applications in the different types of the fields that can be categorized as the follows –
i. Aero – space technology.
ii. Air – line aviation.
iii. Criminology.
iv. Education.
v. Security analysis.
vi. Port – folio management.
vii. Personnel management.
viii. Manufacturing design and the assembly.
ix. Food industry.
x. Health care management.
xi. Geo – logical data analysis.
xii. Interpreting the oil exploration drilling sites.
xiii. Tax planning.
xiv. Quality control.
xv. Quality monitoring.
xvi. Strategic goal setting.
xvii. Configuring the various computer systems.
xviii. Trouble shooting telephone network.
xix. Gene – cloning experiments.
xx. Foreign exchange management.

What are the Capabilities and Characteristics of the Expert Systems?

Capabilities of the Expert Systems
1. Capturing of the expertise.
2. Codifying the expertise.
3. Duplicating the expertise.
4. Transferring the expertise.
5. Saving the human effort’s time.
6. Saving on the maintenance.
7. Up – dating the knowledge base on the regular basis.

Characteristics of the Expert Systems
1. Should be able to display the intelligent behavior.
2. Should be able to explain the reasoning.
3. Should be able to draw the conclusions from the relationships that are very complex in the nature.
4. Should be able to provide the much needed portable knowledge.
5. Should be able to deal with the certainty.
6. Is not used or tested much due to the reason which says that it is difficult to use.
7. Does not possess the ability to deal with the mixed knowledge.
8. Cannot refine own knowledge base.
9. Are very much difficult to maintain.
10. Limited to the narrow problems.

What are Expert Systems?

In today’s world, every company or its management or any individual in same way or the other is dependent on the use of the computer and its various applications. It was the decade of the 1980’s when the coming up of the expert systems was observed by the different users of the world. The experts systems are one of the most enjoy – able applications of the computer and help a great deal in the transformation of the way the corporations developed their software.

The first commercially acclaimed expert system was DEC’s ‘XCON and this was done in the year 1981. It was in the year 1983 when for the first time the expert systems building tools were offered for the sale. But after this year i.e. in the year 1984, the number of the successfully fielded expert systems mushroomed and this mainly occurred because of the high level development tools, which at that time became very much widely available. The years that followed this scenario i.e. in the year 1985 and the year 1986, observed a very large and a very good response from the various types of the users and these were at that time referred to as the hot years but after these years a great dip was observed in the graph of response from the users and these were referred to as the cold years.

But it was the decade of the 1990’s when a huge response was observed and the market of the expert systems developed a lot and during this, the expert systems were largely accepted by almost all type of the users. The expert system technology is mainly based on the research discipline of the artificial intelligence. This artificial intelligence is actually a branch of the computer science and mainly deals with the design and the implementation of the different types of the programs.

Meaning and the Definition Of Expert Systems
From the time of the origin of the expert systems, different types of the persons who use it i.e. the users tend to have an under – standing about the expert system depending on the type of the work in which that particular user is using the expert system. Hence, it can be said that the different users have different definitions of the expert system. There is no particular definition of the expert system which has the ability to completely fulfill or satisfy all the queries of the various users.

According to Peter Jackson, “an expert system can be defined as the computer program that has the ability to represent and reason with the knowledge of some of the particular subject specialist with a view to solving problems or giving any type of the advice.

In general an expert system can be referred to as the technology that has the ability to make the computer programming very easier in the nature and also very effective in the working. The expert system also helps in carrying out the transformation in the computing with the help of the movement of the various programming techniques beyond the numerical programming into a realm of the logical, symbolic programming.

A very better view about the expert systems can be obtained by under – standing the concept of the expert system given by Robert Barwoman and David Glover. According to both of them, expert system can be defined as the “highly specialized computer systems having the ability of stimulating that particular element of the human specialist’s knowledge and reasoning that can be formulated into the knowledge chunks, characterized by a set of the human facts and the different heuristic rules.

According to Bruce Buchanan and Reid Smith, an expert system can be defined as the computer program that –
1. Has the ability to explain both what it knows and the reasons for its answers.
2. Performs well in the problem area.
3. Reasons with the domain – specific knowledge.
4. Uses the domain – specific methods that are heuristic in the nature and are also following the different types of the procedures that are algorithmic.
5. Has the ability to retain the flexibility.

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