Analytical applications. Peripheral devices perform the function of a control of the operation of a computer according to a given program b input / output of information in the operational storage of information d processing of data entered into a computer The final stage of the existence of an expert with

Expert system is a system artificial intelligence built on the basis of deep special knowledge about a certain subject area (obtained from experts in this area). Expert systems are one of the few types of artificial intelligence systems that are widely used and found practical use... There are expert systems for military affairs, geology, engineering, computer science, space technology, mathematics, medicine, meteorology, industry, agriculture, management, physics, chemistry, electronics, law, etc. And only the fact that expert systems remain very complex, expensive, and most importantly, highly specialized programs, hinders their even wider distribution.

The technology of expert systems is one of the directions of a new area of ​​research, which has been called artificial intelligence (AI). Research in this area focuses on the development and implementation of computer programs able to emulate (imitate, reproduce) those areas of human activity that require thinking, a certain skill and accumulated experience. These include the tasks of decision making, pattern recognition, and understanding human language. This technology has already been successfully applied in some areas of technology and social life - organic chemistry, prospecting for minerals, medical diagnostics. The list of typical tasks solved by expert systems includes:

• extracting information from raw data (such as signals from sonar);
• fault diagnosis (as in technical systems and in the human body);
• structural analysis of complex objects (for example, chemical compounds);
• choice of configuration of complex multicomponent systems (for example, distributed computer systems);
• planning the sequence of operations leading to a given goal (for example, performed by industrial robots).

Features of expert systems

• competence - in a specific subject area, the expert system must reach the same level as human specialists; at the same time, it should use the same heuristic techniques, and also deeply and widely reflect the subject area;

• symbolic reasoning - the knowledge on which the expert system is based, represent in a symbolic form the concepts of the real world, reasoning also occurs in the form of a transformation of symbolic sets;

• depth - the expertise must solve serious, non-trivial tasks, characterized by the complexity of the knowledge that the expert system uses, or the abundance of information; this does not allow the use of a full enumeration of options as a method for solving a problem and forces one to resort to heuristic, creative, informal methods;

• self-awareness - the expert system must include a mechanism to explain how it comes to the solution of the problem.

Expert systems are created to solve all sorts of problems, but they have a similar structure (Fig. 8); the main types of their activities can be grouped into the categories shown in table. 2.

Rice. 1. Scheme of a generalized expert system

Table 1. Typical categories of expert systems applications

Functions performed by the expert system

Not every knowledge-based system can be considered as an expert system. The expert system must also be able to somehow explain their behavior and their decisions to the user, just as a human expert does. This is especially necessary in areas that are characterized by uncertainty, inaccuracy of information (for example, in medical diagnostics). In these cases, the ability to explain is needed in order to increase the user's confidence in the advice of the system, as well as to enable the user to discover possible defect in the reasoning of the system. In this regard, expert systems should provide for friendly interaction with the user, which makes the process of reasoning of the system "transparent" for the user.

Often an additional requirement is imposed on expert systems - the ability to deal with uncertainty and incompleteness. Information about the task at hand may be incomplete or unreliable; relations between objects of the subject area can be approximate. For example, it may not be completely certain that a patient has a symptom or that the measured data are correct; the medication can cause complications, although this usually does not happen. In all these cases, reasoning using a probabilistic approach is required.

In the most general case, in order to build an expert system, we must develop mechanisms for performing the following system functions:

• solving problems using knowledge about a specific subject area - perhaps, in this case, there will be a need to deal with uncertainty;
• interaction with the user, including an explanation of the intentions and decisions of the system during and after the end of the process of solving the problem.

Each of these functions can be very complex and depend on the application area as well as different practical requirements. A variety of difficult problems can arise during the design and implementation process. Here we limited ourselves to outlining the main ideas that are subject to further detailing and improvement.

The structure of expert systems

Fig. 2. Expert system architecture

Classes of expert systems

According to the degree of complexity of the tasks being solved, expert systems can be classified as follows:

According to the method of forming a solution, expert systems are divided into two classes: analytical and synthetic... Analytical systems involve the choice of solutions from a set of known alternatives (determination of the characteristics of objects), and synthetic systems - the generation of unknown solutions (formation of objects).

According to the method of accounting for a time attribute, expert systems can be static or dynamic... Static systems solve problems with unchanged data and knowledge in the process of solving, dynamic systems allow such changes. Static systems carry out a monotonous uninterrupted solution of the problem from the input of initial data to the final result, dynamic systems provide for the possibility of revising the previously obtained results and data in the process of solving.

According to the types of data and knowledge used, expert systems are classified into systems with deterministic (well-defined) knowledge and uncertain knowledge... Uncertainty of knowledge (data) is understood as their incompleteness (absence), unreliability (inaccuracy of measurement), ambiguity (ambiguity of concepts), fuzziness (qualitative assessment instead of quantitative).

According to the number of knowledge sources used, expert systems can be built with using one or many sources of knowledge... Sources of knowledge can be alternative (many worlds) or complementary to each other (cooperating).

The most famous / common ES

• CLIPS is a very popular ES (public domain)
• OpenCyc is a powerful dynamic ES with a global ontological model and support for independent contexts
• WolframAlpha - Search Engine, Intelligent "Knowledge Computing Engine"
• MYCIN is the most famous diagnostic system, which is designed to diagnose and monitor the patient's condition with meningitis and bacterial infections.
• HASP / SIAP is an interpretive system that determines the location and types of ships in the Pacific Ocean from data

acoustic tracking systems.

Stages of expert system design

Currently, a certain technology for the development of ES has developed, which includes the following six stages:

• Receptions	Description
  1. Observation	The engineer observes, without interfering, how the expert solves a real problem
  2. Discussion of the task	An engineer informally discusses data, knowledge and solution procedures with an expert on a representative set of tasks
  3. Description of the task	An expert describes how to solve problems for typical queries
  4. Analysis of the solution	The expert comments on the obtained results of solving the problem, detailing the line of reasoning
  5. System check	The expert offers the engineer a list of tasks for solving (from simple to complex), which are solved by the developed system
  6. System investigation	The expert examines and criticizes the structure of the knowledge base and the operation of the inference engine
  7. Assessment of the system	The engineer invites new experts to evaluate the solutions of the developed system

  table 2

  The first two stages of the development of an expert system constitute a logical stage, not associated with the use of a well-defined tool. The subsequent steps are implemented as part of the physical creation of the project based on the selected tool. At the same time, the process of creating an expert system as a complex software product, it makes sense to carry out using the prototypal design method, the essence of which boils down to a constant increase in the knowledge base, starting from the logical stage.

Stage three. Loading is complete. As you can see in Figure 12.6, the tool menu has been added new tab called "Advanced Process".

This is similar to loading theme panels in Visio. However, ARENA is not a "drawing", but a powerful tool simulation.

ARENA software allows you to create diagrams that reflect the functioning of a process. The process of creating diagrams is in many ways similar to that in MS Visio. It also uses technology Drag and drop, however, for some, the process of "drawing" in MS Visio will be more convenient and preferable.

Central component expert system is a knowledge base that acts in relation to other components as a meaningful subsystem that constitutes the main value.

Knowledge base is a set of units of knowledge that are formalized using a certain method knowledge representation reflection of the objects of the problem area and their interrelationships, actions on objects and, possibly, the uncertainties with which these actions are carried out.

As methods knowledge representation most often, either rules, or objects (frames), or a combination of these are used. So, the rules are constructions:

If< условие >That<заключение>CF (certainty factor)<значение>

The factors of certainty (CF), as a rule, are either conditional probabilities Bayesian approach (from 0 to 1), or the confidence coefficients of fuzzy logic (from 0 to 100).

Examples of rules are as follows.

Rule 1: If the ROI> 0.2, then ROI = "fair" CF 100.

Rule 2: if Debt = "no" and Profitability = "Satisfactory", then Financial Condition = "Satisfactory" CF 80.

Rule 3: If Financial Condition = Satisfactory and Reputation = Satisfactory then Business Credibility = Satisfactory CF 90.

Objects are a collection of attributes that describe properties and relationships with other objects. Unlike database records, each object has unique name... Some of the attributes reflect typed relationships, such as "kind - kind" (super-class - sub-class), "whole - part", etc. Instead of specific values object attributes can be set to default values ​​that are specific to entire object classes or attached procedures (process).

Intelligent interface... The exchange of data between the end user and the ES is performed by an intelligent interface program that perceives user messages and converts them into the form of a knowledge base representation and, conversely, translates internal representation the result of processing in the user format and issues a message to the required medium.

The most important requirement for organizing a dialogue between the user and the ES is naturalness, which does not literally mean the formulation user needs natural language sentences, although this is not excluded in some cases.

It is important that the sequence of solving the problem is flexible, consistent with the user's perceptions and conducted in professional terms.

Withdrawal mechanism. This software toolkit receives a request converted into an internal representation from the intelligent interface, forms a specific algorithm for solving the problem from the knowledge base, executes the algorithm, and the resulting result is provided to the intelligent interface to respond to the user's request. The application of any inference mechanism is based on the process of finding, in accordance with the goal and the description of a specific situation (initial data), related to the solution of units of knowledge (rules, objects, precedents, etc.) and linking them, if necessary, into a chain of reasoning leading to a definite result. For knowledge representation in the form of rules, this can be a direct or reverse chain of reasoning (Figure 12.10 and Figure 12.11).

For object oriented knowledge representation the use of the mechanism of inheritance of attributes is typical, when the values ​​of attributes are passed along the hierarchy from the higher-level classes to the lower-level ones. Also, when the frame attributes are filled with the necessary data, the attached procedures are launched for execution.

Explanation mechanism. In the process or as a result of solving the problem, the user can request an explanation or justification of the solution progress. To this end, the ES should provide an appropriate explanation mechanism.

The explanatory abilities of the ES are determined by the ability of the inference mechanism to remember the way of solving the problem. Then the user's questions "How?" and why?" a solution is received or certain data are requested, and the system can always issue a chain of reasoning to the required checkpoint, accompanying the issuance of an explanation with pre-prepared comments. In the absence of a solution to the problems, an explanation should be issued to the user automatically.

It is useful to have the possibility of a hypothetical explanation of the solution to the problem, when the system answers the questions about what will happen in this or that case. However, the user is not always interested in the complete output of the solution, which contains many unnecessary details. In this case, the system should be able to select only key points from the chain, taking into account their importance and the user's level of knowledge. To do this, the knowledge base needs to maintain a model of user knowledge and intentions.

If the user still does not understand the received answer, then the system should be able to teach the user certain fragments of knowledge in a dialogue based on the supported model of problem knowledge, i.e. to reveal in more detail individual concepts and dependencies, even if these details were not used directly in the conclusion.

Knowledge acquisition mechanism. Knowledge base reflects knowledge experts(specialists) in this problem area about actions in various situations or processes of solving typical problems. The identification of such knowledge and their subsequent presentation in the knowledge base is carried out by specialists called knowledge engineers... To enter knowledge into the database and then update it, the ES must have a mechanism for acquiring knowledge. In the simplest case, an intelligent editor is used, which allows you to enter units of knowledge into the base and carry out their syntactic and semantic control, for example, for consistency. In more complex cases, the knowledge engineer must extract knowledge through special scenarios of interviewing experts, or from input examples of real situations, as in the case of inductive inference, or from texts, or from work experience itself intelligent system.

Classes of expert systems

By the degree of complexity of the tasks being solved expert systems can be classified as follows.

By the method of forming the decision expert systems are divided into two classes: analytical and synthetic... Analytical systems involve the choice of solutions from a variety of known alternatives (determination of the characteristics of objects), and synthetic systems - the generation of unknown solutions (formation of objects).

By the method of accounting for a temporary indicator expert systems may be static or dynamic... Static systems solve problems with data and knowledge unchanged during the solution process, dynamic systems allow for such changes. Static systems carry out a monotone uninterrupted solution of a problem from inputting initial data to the final result, dynamic systems provide for the possibility of revision in the process of solving the previously obtained results and data.

By types of data and knowledge used expert systems classified into systems with deterministic(well-defined) knowledge and uncertain knowledge. The uncertainty of knowledge is understood as their incompleteness, unreliability, ambiguity, and fuzziness.

By the number of sources of knowledge used expert systems can be built using one or multiple sources of knowledge. Sources of knowledge can be alternative or complementary.

In accordance with the listed features of the classification, the following main classes of expert systems are distinguished (Table 12.1.).

Classifying expert systems. Expert systems solving problems of situation recognition are called classifying, since they determine the belonging of the analyzed situation to a certain class.

As the main method of forming decisions, the method of logical deductive inference from general to particular is used, when a particular conclusion is obtained by substituting the initial data into a certain set of interrelated general statements.

Redefining expert systems... A more complex type of analytical tasks is represented by tasks that are solved on the basis of uncertain initial data and applied knowledge. In this case expert system should, as it were, redefine the missing knowledge, and in the space of solutions, several possible solutions with varying likelihood or certainty in the need for their implementation.

Bayesian probabilistic approach and fuzzy logic can be used as methods for dealing with uncertainties.

Additional defining expert systems can use several sources of knowledge to form a solution. In this case, heuristic methods of choosing knowledge units from their conflicting set can be applied, for example, based on the use of priority priorities, or the obtained degree of certainty of the result, or the values ​​of preference functions, etc.

For analytical tasks of the classifying and redefining types, it is characteristic the following areas of concern.

1. Interpreting data- choice of a solution from a fixed set of alternatives based on the entered information about the current situation. The main purpose is to determine the essence of the situation under consideration, the choice of hypotheses based on their facts. A typical example is expert system analysis of the financial condition of the enterprise.
2. Diagnostics- identification of the reasons that led to the occurrence of the situation. A preliminary interpretation of the situation is required, followed by verification of additional facts, for example, identifying factors that reduce production efficiency.
3. Correction- diagnostics, supplemented by the possibility of assessing and recommending actions to correct deviations from the normal state of the situations under consideration.

Transforming expert systems... In contrast to analytical static expert systems, synthesizing dynamic expert systems imply a repetitive transformation of knowledge in the process of solving problems, which is associated with the nature of the result, which cannot be predetermined in advance, as well as with the dynamism of the problem area itself.

For synthesizing dynamic expert systems, the following are most applicable problem areas.

1. Design- defining the configuration of objects in terms of achieving the specified performance criteria and constraints, such as designing an enterprise budget or investment portfolio.
2. Forecasting- prediction of the consequences of the development of current situations on the basis of mathematical and heuristic modeling, for example, forecasting trends in exchange trading.
3. Dispatching- the distribution of work in time, scheduling, for example, scheduling the development of capital investments.
4. Planning- the choice of a sequence of user actions to achieve the goal, for example, process planning delivery of products.
5. Monitoring- tracking the current situation with possible subsequent correction. For this, diagnostics, forecasting, and, if necessary, planning and correcting user actions are carried out, for example, monitoring the sales of finished products.
6. Control- monitoring, supplemented by the implementation of actions in automatic systems, for example, decision-making in exchange trading.

Multi-agent expert systems. Such dynamic systems are characterized by the integration in the knowledge base of several heterogeneous sources of knowledge that exchange the results obtained with each other. dynamic basis, for example, through a "message board".

The following features are characteristic of multi-agent systems:

• conducting alternative reasoning based on the use of various sources of knowledge with a mechanism for eliminating contradictions;
• distributed problem solving, which are broken down into parallel solved subproblems corresponding to independent sources of knowledge;
• application of a variety of strategies for the operation of the mechanism for drawing conclusions, depending on the type of problem being solved;
• processing large amounts of data contained in the database;
• the ability to interrupt the solution of problems due to the need to obtain additional data and knowledge from users, models, and parallel subproblems to be solved.

The subject areas need expert systems: medicine, pharmacology, chemistry, geology, economics, jurisprudence, etc., in which most of the knowledge ... 1) is the personal experience of specialists high level 2) can be reduced to a system of machine instructions and implemented on a computer 3) has already been obtained and it is possible to refuse direct human participation and transfer the ability to make decisions to a computer 4) requires finding optimal indicators for a specific task of a given industry
The correct answer is 1.

1) commercial system 2) research prototype 3) working prototype 4) industrial system
The correct answer is 1.

Expert systems are used when ...
The correct answer is 1.

The correct answer is 1.

1) it is necessary to solve the problem in an environment hostile to humans 2) the problem needs to be solved a limited number of times 3) there is a sufficient number of experts to solve this range of problems 4) solving the problem with the help of a human expert is less time consuming and more complete in scope
The correct answer is 1.

The correct answer is 1.

A characteristic feature of any expert system that distinguishes it from other computer information systems, is an... 1) the ability for self-development 2) sorting, fetching data at the request of users 3) the use of methods that make it possible to reduce the solution of any problem to a specific set of machine instructions 4) providing multiple access to information
The correct answer is 1.

The correct answer is 1.

The correct answers are 1, 2.

The system software included ... 1) programs responsible for interacting with specific devices 2) programs responsible for interaction with the user 3) means of ensuring computer security 4) means of automating work on checking, adjusting and configuring a computer system
The correct answers are 1, 2.

1) computer-aided design systems 2) expert systems 3) magnetic disk maintenance programs 4) system recovery programs
The correct answers are 1, 2.

The functions of the basic software are ... 1) checking the composition and operability of the computing system 2) displaying diagnostic messages 3) providing user interface 4) expanding the functions of the operating system
The correct answers are 1, 2.

The application software includes ... 1) Web editors 2) desktop publishing systems 3) antivirus software 4) data compression tools
The correct answers are 1, 2.

BIOS (Basic Input Output System)is an... 1) a group of programs in read-only memory 2) a standard code table 3) part random access memory 4) the base part of the microprocessor
The correct answer is 1.

A device that connects administratively independent communication networks is ... 1) router 2) host 3) domain 4) hub.
The correct answer is 1.

Network operating systems are a set of programs that ... 1) ensure the simultaneous operation of a group of users 2) users transfer them on the network from one computer to another 3) ensure the processing, transmission and storage of data on the computer 4) expand the capabilities of multitasking operating systems
The correct answer is 1.

Address set Email on the Internet - [email protected] The name of the mail service in it is 1) mail 2) pochta 3) mail.ru 4) ru
The correct answer is 1.

Internet Proxy Server ... 1) provides anonymization of access to various resources 2) provides the user with a secure communication channel 3) allows encryption of electronic information 4) is used for exchange electronic signatures between network subscribers
The correct answer is 1.

A gateway is a device that ... 1) allows you to organize data exchange between two networks using different communication protocols 2) allows you to organize data exchange between two networks using the same communication protocol 3) connects networks different types but using one operating system 4) connects workstations
The correct answer is 1.

The network protocol is ... 1) PPP 2) WWW 3) ECP 4) URL
The correct answer is 1.
Remarks. PPP (Point to Point Protocol) is a data link protocol that allows you to use regular modem lines to access the Internet. ECP (Enhanced Capability Port) is a port with enhanced capabilities. A URL (Uniform Resource Locator) is a uniform identifier for the location of a resource. It is a standardized way to record the address of a resource on the Internet. WWW (World Wide Web - World Wide Web) is a distributed system that provides access to related documents located on various computers connected to the Internet.

The Internet Service Provider is ... 1) provider 2) computer connected to the Internet 3) browser 4) modem connected to the Internet
The correct answer is 1.

In accordance with the standard, the speed of information transmission over the network can be measured in ... 1) kbps 2) kb / min 3) kb / min 4) kb / s
The correct answer is 1.

To quickly jump from one www-document to another, use ... 1) hyperlink 2) browser 3) website 4) tag
The correct answer is 1.

The document is requested from the university website page at the following address: http: //university.faculty.edu/document.txt. The domain name of the computer in which the document is located is ... 1) university.faculty.edu 2) university 3) faculty 4) university.faculty
The correct answer is 1.

A computer connected to the Internet must be ... 1) get an IP address 2) have a web server installed 3) get Domain name 4) have a website hosted on it
The correct answer is 1.

To browse web pages use ... 1) browsers 2) Internet portals 3) firewalls 4) hashing programs
The correct answer is 1.

The most effective means of monitoring data on the network are ... 1) passwords, ID cards and keys 2) archiving systems 3) RAID disks 4) antivirus software
The correct answer is 1.

A bridge is a device that connects ... 1) two networks using the same data transmission methods 2) two networks having the same server 3) workstations of the same network 4) subscribers of a local computer network
The correct answer is 1.

In order to establish an exchange by email digitally signed must be sent to the recipient of the messages ... 1) public encryption key 2) private key encryption 3) kind of your digital signature 4) the encryption algorithm you are using
The correct answer is 1.

Local topologies computer networks are ... 1) star, bus, ring 2) chamomile, sphere, star 3) server, domain, terminal 4) corporate, administrative, mixed
The correct answer is 1.

Most effective way protection local computer from unauthorized access when it is turned on is ... 1) using software and hardware protection 2) setting a password on the BIOS 3) setting a password on the operating system 4) using the latest operating system
The correct answer is 1.

A computer connected to the Internet can have the following two addresses: 1) digital and domain 2) digital and user 3) character and domain 4) forward and backward
The correct answer is 1.

Various services are used on the Internet: e-mail, newsgroups, Internet pager, online store, etc. The service system with which you can communicate via the Internet with other people in real time is named ... 1) IRC 2) Windows Chat 3) Slideshare 4) FTP
The correct answer is 1.

The instant messaging system over the Internet is called ... 1) ICQ 2) IRC 3) URL 4) GPS
The correct answer is 1.

The FTP network service is designed for ... 1) moving data between different operating systems 2) conducting video conferencing 3) viewing web pages 4) "downloading" messages and attached files
The correct answer is 1.

The most effective way to protect a local computer from unauthorized access when it is turned on is ... 1) using software and hardware protection 2) setting a password on the BIOS 3) setting a password on the operating system 4) using the latest operating system
The correct answer is 1.

As you know, a computer's IP address consists of four numbers separated by dots. Each of the numbers of the IP address can take decimal values ​​from 0 to ... 1) 255 2) 256 3) 999 4) 192
The correct answer is 1.

You need to send an email to the remote recipient. In this case, the recipient must know that this is exactly the same message. To do this, you need ... 1) use a digital signature 2) send a message via a secret communication channel 3) archive the message 4) close the message with a password
The correct answer is 1.

In order to establish the exchange of digitally signed electronic messages, you must send the recipient of messages ... 1) public encryption key 2) private encryption key 3) type of your digital signature 4) encryption algorithm you use
The correct answer is 1.

To search for information on the Internet using search engines(e.g. Google, Rambler, Yandex, Yahoo!) users ask ... 1) keywords 2) tags 3) search words 4) dictionary words
The correct answer is 1.

Internet e-mail address is set - [email protected] By the name of the owner of this email address is ... 1) postbox 2) yandex 3) yandex.ru 4) [email protected]
The correct answer is 1.

The WAREHOUSE database table, containing 5 columns of information about the product (name, supplier, quantity, expiration date, price), contains information about 25 types of goods. The number of records in the table is ... 1) 25 2) 5 3) 125 4) 30
The correct answer is 1.

The basis of any intelligent expert system is ... 1) knowledge base 2) mathematical model 3) a system of rules for solving the problem 4) control system
The correct answer is 1.

The subject areas need expert systems: medicine, pharmacology, chemistry, geology, economics, jurisprudence, etc., in which most of the knowledge ... 1) is the personal experience of high-level specialists 2) can be reduced to a system of machine instructions and implemented on computer 3) has already been obtained and it is possible to refuse direct human participation and transfer the ability to make decisions to a computer 4) requires finding optimal indicators for a specific task in a given industry
The correct answer is 1.

The final stage of the existence of the expert system is ... 1) commercial system 2) research prototype 3) working prototype 4) industrial system
The correct answer is 1.

Expert systems are used when ... 1) the initial data are well formalized, but special extensive knowledge is required to make a decision; 2) the initial data are compact and convenient for implementation on a computer; 3) it is required to find optimal indicators (for example, finding minimum costs or determining the maximum profit) 4) objects, processes or phenomena are investigated by building and studying models to determine or refine the characteristics of the original
The correct answer is 1.

The similarity of expert systems with other applications is that they ... 1) are designed to solve a certain range of tasks 2) they use heuristic methods as the main methods for solving the problem 3) at the stage of solving the problem, certain facts and conclusions are formed 4) they model the thinking of a person, and not the specific nature of the subject area
The correct answer is 1.

The use of an expert system is advisable if ... 1) it is necessary to solve the problem in an environment hostile to humans 2) the problem needs to be solved a limited number of times 3) there is a sufficient number of experts to solve this range of problems 4) solving the problem with the help of a human expert is less time consuming and more complete in scope
The correct answer is 1.

The core of the expert system is not implemented on ... 1) hypertext markup languages ​​2) declarative programming languages ​​3) imperative programming languages ​​4) ontology presentation languages
The correct answer is 1.

A characteristic feature of any expert system that distinguishes it from other computer information systems is ... 1) the ability for self-development 2) sorting, data selection at the request of users 3) the use of methods that allow reducing the solution of any problem to a specific set of machine instructions 4 ) providing multiple access to information
The correct answer is 1.

The main classes of expert systems are ... 1) fault diagnosis systems 2) meteorological systems 3) database management systems 4) geolocation systems
The correct answer is 1.

The software (software) of computing systems includes ... 1) system software 2) service software 3) functional software 4) information software
The correct answers are 1, 2.

Expert systems are complex software systems that accumulate the knowledge of specialists in specific subject areas and replicate this empirical experience for the advice of less qualified users.

The areas of application of knowledge-based systems are very diverse: business, manufacturing, military applications, medicine, sociology, geology, space, agriculture, management, jurisprudence, etc.

Knowledge-based systems (KOPs) are software systems, the main building blocks of which are knowledge base and inference engine... Among the POPs are:

• intelligent information retrieval systems;
• expert systems (ES).

Intelligent information retrieval systems differ from the previous generation of information retrieval systems not only by a much more extensive reference and information fund, but also by the most important ability to form adequate responses to user queries even when the queries are not of a direct nature.

The best known practical example of POPs is expert systems capable of diagnosing diseases, assessing potential mineral deposits, performing natural language processing, speech and image recognition, etc. Expert systems are the first step in the practical implementation of research in the field of artificial intelligence

The basic structure of the expert system is shown in the figure below.

The structural elements that make up the expert system perform the following functions.

Knowledge base implements the functions of representing knowledge in a specific subject area and managing them.

Inference engine makes inferences based on the knowledge available in the knowledge base.

User interface is necessary for the correct transmission of answers to the user, otherwise it is extremely inconvenient to use the system.

Knowledge acquisition module is necessary to obtain knowledge from an expert, support the knowledge base and supplement it if necessary.

Answer and explanation module forms the conclusion of the expert system and submits various comments attached to the conclusion, as well as explains the reasons for the conclusion.

The structure of the expert system.

The listed structural elements are the most characteristic, although in real expert systems their functions can be appropriately strengthened or expanded.

Knowledge in the knowledge base is presented in a specific form and the organization of the knowledge base makes it easy to define, modify and replenish. Solving problems using logical inference based on knowledge stored in the knowledge base is implemented by an autonomous inference mechanism. Although both of these components of the system are independent from the point of view of its structure, they are closely related to each other and the definition of the knowledge representation model imposes restrictions on the choice of the appropriate inference mechanism.

Advantages expert systems:

• Constancy... Expert systems forget nothing, unlike a human expert.
• Reproducibility... Any number of copies of the expert system can be made, and training new experts is time-consuming and expensive.
• Efficiency. Can increase productivity and reduce personnel costs.
• Constancy... Using expert systems, such transactions are processed in the same way. The system will make comparable recommendations for similar situations.
• Impact on people... New effect (the most up-to-date information that affects common sense). Main effect (early information dominates common sense).
• Documentation. The expert system can document the decision process.
• Completeness... An expert system can review all transactions, while a human expert can review only a single sample.
• Timeliness... Errors in designs and / or can be found in a timely manner.
• Latitude... The knowledge of many experts can be combined to give the system more breadth than a single person is likely to achieve.
• Risk reduction business management thanks to the consistency of decision making, documentation and competence.

Disadvantages of expert systems:

• Common sense... In addition to broad technical knowledge, the human expert has common sense. It is not yet known how to put common sense into expert systems.
• Creative potential... A human expert can react creatively to unusual situations, expert systems cannot.
• Education... The human expert will automatically adapt to the changing environment; expert systems need to be explicitly modified.
• Sensory experience... The human expert has a wide range of sensory experiences; expert systems are currently based on character input.

Expert systems are not good if there is no solution or when the problem lies outside their area of ​​expertise.

The class of expert systems today unites several thousand different software systems that can be classified according to various criteria: the problem being solved, communication with real time, the type of computer, the degree of integration.

Expert systems development methodology

The development of intelligent information systems is different from the creation of a conventional software product. The experience of developing early expert systems has shown that the use of traditional programming technology either excessively delays the development process, or generally leads to a negative result. This is mainly due to the need to modify the principles and methods of construction as the knowledge of the developers about the problem area increases.

It is known that most of the knowledge in a specific subject area remains the personal property of an expert. The greatest problem in the development of an expert system is the procedure for obtaining knowledge from an expert and entering it into the knowledge base, called knowledge extraction. This happens not because he does not want to divulge his secrets, but because he is not able to do this - after all, the expert knows much more than he himself realizes. To identify the expert's knowledge and formalize it throughout the entire development period, the knowledge engineer interacts with him.

To avoid costly and unsuccessful attempts, a set of guidelines have been developed to determine if a problem is suitable for an expert system solution:

• The need for a solution must match the cost of developing it. The costs and benefits obtained must be realistic.
• It is impossible to use the knowledge of a human expert where it is needed. If “expert” knowledge is widespread, then it is unlikely that it is worth developing an expert system. However, in areas such as oil exploration and medicine, there may be rare specialized knowledge that can be inexpensively equipped with an expert system and not used a very highly paid expert.
• The problem can be solved using symbolic methods of reasoning.
• The problem is well structured and does not require common sense knowledge. Common sense knowledge is well known, so there is no need to capture and represent it.
• The problem cannot be easily solved using more traditional computational methods. If there is a good algorithmic solution to the problem, you should not use an expert system.
• There are experts in this problem area. Since an expert system is designed to work successfully, it is essential that experts are willing to help design it rather than feel threatened. In addition, the support of the administration and potential users is needed.
• The problem is of the right size and scope. As a rule, a problem requires the application of the knowledge of highly specialized experts, but a human expert should spend a short time, at most an hour, on solving it.

Currently, there is a sequence of actions in the development of expert systems. It includes the following steps: identification, knowledge acquisition, conceptualization, formalization, implementation, testing and trial operation.

Rice. 10.2. Expert systems development technology

Identification

The identification stage is associated, first of all, with the comprehension of the tasks to be solved by the future expert system, and the formation of requirements for it. At this stage, the development of a prototype of the system is planned, the sources of knowledge (books, experts, methods), goals (dissemination of experience, automation of routine operations), classes of problems to be solved, etc. are determined. The result identification is the answer to the question of what needs to be done and what resources need to be used.

The acquisition of knowledge

When solving the problem of acquiring knowledge, three strategies are distinguished: acquiring knowledge, extracting knowledge and discovering knowledge.

Acquisition of knowledge is understood as a method of automated filling of the knowledge base through a dialogue between an expert and a special program.

Knowledge elicitation is the procedure of interaction between a knowledge engineer and a knowledge source (expert, specialized literature, etc.) without the use of computer technology.

The terms "knowledge discovery" and Data mining associated with the creation of computer systems that implement methods of automatic knowledge acquisition.

Conceptualization

At the stage conceptualizing a meaningful analysis of the problem area is carried out, the concepts used and their interrelationships are identified, methods for solving problems are determined. This stage ends with the creation of a domain model that includes the main concepts and relationships. The model is presented in the form of a graph, table, diagram or text.

Formalization

At the stage formalization all key concepts and relations are expressed in some formal language, which is chosen from among the existing ones, or is created anew. In other words, at this stage, the composition of the means and methods of presenting declarative and procedural knowledge are determined, this representation is carried out and, as a result, a description of the solution to the problem of the expert system is created on the selected formal language.

Execution (implementation)

At the stage fulfillment one or several really working prototypes of the expert system are created. Various tools are now widely used to speed up this process.

Testing

At this stage, the work of the prototype program is evaluated and checked in order to bring it in line with the real needs of users. The prototype is checked for the following main positions:

• convenience and adequacy of the input-output interfaces (the nature of the questions in the dialogue, the consistency of the output text of the result, etc.);
• the effectiveness of the control strategy (the order of enumeration, the use of fuzzy inference, etc.);
• the correctness of the knowledge base (completeness and consistency of rules).

Stage task testing- identification of errors and development of recommendations for fine-tuning the prototype of the expert system to an industrial design.

Trial operation

At the stage trial operation the suitability of the expert system for the end user is verified. Suitability is mainly determined by the convenience and usefulness of the design. Utility is understood as the ability of the expert system to determine the user's needs during the dialogue, to identify and eliminate the causes of failures in work, as well as to meet the specified user needs (to solve the assigned tasks). Ease of work implies natural interaction with the expert system, flexibility (the ability of the system to adjust to different users, as well as to take into account changes in the qualifications of the same user) and the stability of the system to errors (the ability not to fail in case of erroneous user actions).

After successful completion of the stage trial operation an expert system is classified as a commercial system suitable not only for its own use, but also for sale to various consumers.

Expert systems construction tools

Currently, there are tools that accelerate the design and development of ES. They are called instrumentation, or just tools. In other words, under instrumentation understand the combination of hardware and software that enables the creation of knowledge-based applications.

Among the program tools the following large groups are distinguished:

• symbolic programming languages ​​(LISP, INTERLISP, SMALLTALK);
• knowledge engineering languages, that is, programming languages ​​that allow one of the ways to represent knowledge (OPS5, LOOPS, KES, Prolog);
• shells of expert systems (or empty expert systems), that is, systems that do not contain knowledge about any subject area (EMYCIN, ECO, EXPERT, EXSYS RuleBook, Expert System Creator, etc.)