CHAPTER 6 - Expert Systems

expert system

is a computer program that is designed to solve complex problems and to provide decision-making ability like a human expert. It performs this by extracting knowledge from its knowledge base using the reasoning and inference rules according to the user queries

1970

The expert system is a part of AI, and the first ES was developed in the year ____, which was the first successful approach of artificial intelligence. It solves the most complex issue as an expert by extracting the knowledge stored in its knowledge base.

Facts, heuristics

The first expert system helped in decision-making for complex problems using both _____ and __________ like a human expert. It is called so because it contains the expert knowledge of a specific domain and can solve any complex problem of that particular domain. These systems are designed for a specific domain, such as medicine, science, etc

assist

It is important to remember that an expert system is not used to replace the human experts. instead, it is used to ______ the human in making a complex decision. These systems do not have human capabilities of thinking and work on the basis of the knowledge base of the particular domain

DENDRAL, MYCIN, PXDES, CaDeT

4 popular examples of expert systems (DMPC)

DENDRAL

example of ES. It was an artificial intelligence project that was made as a chemical analysis expert system. It was used in organic chemistry to detect unknown organic molecules with the help of their mass spectra and knowledge base of chemistry

MYCIN

example of ES. It was one of the earliest backward chaining expert systems that was designed to find the bacteria causing infections like bacteraemia and meningitis. It was also used for the recommendation of antibiotics and the diagnosis of blood clotting diseases.

PXDES

example of ES. It is an expert system that is used to determine the type and level of lung cancer. To determine the disease, it takes a picture from the upper body, which looks like the shadow. This shadow identifies the type and degree of harm.

CaDeT

example of ES. This expert system is a diagnostic support system that can detect cancer at early stages.

High performance, understandable, reliable, highly responsive

4 characteristics of an ES (HURH)

High Performance

characteristic of an ES. The expert system provides high performance for solving any type of complex problem of a specific domain with high efficiency and accuracy.

Understandable

characteristic of an ES. It responds in a way that can be easily understandable by the user. It can take input in human language and provides the output in the same way

Reliable

characteristic of an ES. It is much reliable for generating an efficient and accurate output

Highly responsive

characteristic of an ES. ES provides the result for any complex query within a very short period of time

UI, inference engine, knowledge base

3 components of an ES (UIK)

UI

component of an ES. With the help of this, the expert system interacts with the user, takes queries as an input in a readable format, and passes it to the inference engine. After getting the response from the inference engine, it displays the output to the user. In other words, it is an interface that helps a non-expert user to communicate with the expert system to find a solution.

Inference engine

component of an ES. It is the main processing unit of the system where it applies inference rules to the knowledge base to derive a conclusion or deduce new information. It helps in deriving an error-free solution of queries asked by the user.

Deterministic, probabilistic

two types of inference engine

Deterministic

type of inference engine. The conclusions drawn from this type of inference engine are assumed to be true. It is based on facts and rules.

Probabilistic

type of inference engine. This type of inference engine contains uncertainty in conclusions and is based on the probability

Forward chaining, backward chaining

two modes that an inference engine uses to derive solutions

Forward Chaining

mode used by an inference engine to derive solutions. It starts from the known facts and rules, and applies the inference rules to add their conclusion to the known facts.

Backward Chaining

mode used by an inference engine to derive solutions. It is a backward reasoning method that starts from the goal and works backward to prove the known facts.

Knowledge base

component of an ES. is a type of storage that stores knowledge acquired from the different experts of the particular domain. It is considered as big storage of knowledge. The more the knowledge base, the more precise will be the Expert System.

Knowledge base

component of an ES. It is similar to a database that contains information and rules of a particular domain or subject. One can also view this as collections of objects and their attributes. Such as a Lion is an object and its attributes are it is a mammal, it is not a domestic animal, etc

Factual, heuristic

2 components of knowledge base

Factual

component of knowledge base. The knowledge which is based on facts and accepted by knowledge engineers comes under factual knowledge

heuristic

component of knowledge base. This knowledge is based on practice, the ability to guess, evaluation, and experiences.

Fuzziness

_________ becomes a necessity because Imprecision and uncertainty might arise in various situations and might impact negatively on decision making capacity, so we Introduce imprecision and uncertainty to be involved in decision making.

Fuzzy expert systems

A form of Artificial Intelligence (AI) that uses membership functions and a set of fuzzified inference rules to solve the problems of a particular task or domain

No Memory Limitations

why expert systems. It can store as much data as required and can memorize it at the time of its application. But for human experts, there are some limitations to memorize all things at every time.

High Efficiency

why expert systems. If the knowledge base is updated with the correct knowledge, then it provides a highly efficient output, which may not be possible for a human.

Expertise in a domain

why expert systems. There are lots of human experts in each domain, and they all have different skills, different experiences, and different skills, so it is not easy to get a final output for the query. But if we put the knowledge gained from human experts into the expert system, then it provides an efficient output by mixing all the facts and knowledge

Not affected by emotions

why expert systems. These systems are not affected by human emotions such as fatigue, anger, depression, anxiety, etc.. Hence the performance remains constant.

High security

why expert systems. These systems provide high security to resolve any query

Considers all the facts

why expert systems. To respond to any query, it checks and considers all the available facts and provides the result accordingly. But it is possible that a human expert may not consider some facts due to any reason.

Regular updates improve the performance

why expert systems. If there is an issue in the result provided by the expert systems, we can improve the performance of the system by updating the knowledge base.

Advising

capability of ES. It is capable of advising the human being for the query of any domain from the particular ES.

Provide decision-making capabilities

capability of ES. It provides the capability of decision making in any domain, such as for making any financial decision, decisions in medical science, etc.

Demonstrate a device

capability of ES. It is capable of demonstrating any new products such as its features, specifications, how to use that product, etc

Problem-solving

capability of ES. It has problem-solving capabilities

Explaining a problem

capability of ES. It is also capable of providing a detailed description of an input problem.

Interpreting the input

capability of ES. It is capable of interpreting the input given by the user.

Predicting results

capability of ES. It can be used for the prediction of a result.

Diagnosis

capability of ES. An ES designed for the medical field is capable of diagnosing a disease without using multiple components as it already contains various inbuilt medical tools.

Reproducible, human presence, knowledge, emotions, speed

ADVANTAGES OF EXPERT SYSTEMS

• These systems are highly ____________.

• They can be used for risky places where the _____ ________ is not safe.

• Error possibilities are less if the KB contains correct _________.

• The performance of these systems remains steady as it is not affected by ________, tension, or fatigue.

• They provide a very high _____ to respond to a particular query

Information, creative, costs, acquisition, specific ES, manual

LIMITATIONS OF EXPERT SYSTEMS

• The response of the expert system may get wrong if the knowledge base contains the wrong ___________.

• Like a human being, it cannot produce a ________ output for different scenarios.

• Its maintenance and development _____ are very high.

• Knowledge ___________ for designing is much difficult.

• For each domain, we require a ________ __, which is one of the big limitations.

• It cannot learn from itself and hence requires ______ updates

In designing and manufacturing domain

real life application of ES. used for designing and manufacturing physical devices such as camera lenses and automobiles.

In the knowledge domain

real life application of ES. primary used for publishing the relevant knowledge to the users. The two popular ES used for this domain is an advisor and a tax advisor

In the finance domain

real life application of ES. used to detect any type of possible fraud, suspicious activity, and advise bankers that if they should provide loans for business or not

In the diagnosis and troubleshooting of devices

real life application of ES. for the medicine and IT field

Planning and Scheduling

real life application of ES. used for planning and scheduling some particular tasks for achieving the goal of that task