knowledge base system

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Knowledge base system

Software that uses artificial intelligence or expert system techniques in problem solving processes. It

incorporates a store (database) of expert knowledge with couplings and linkages designed to facilitate its

retrieval in response to specific queries, or to transfer expertise from one domain of knowledge to another.

Knowledge based systems are artificial intelligent tools working in a narrow domain to provide

intelligent decisions with justification. Knowledge is acquired and represented using various knowledge

representation techniques rules, frames and scripts. The basic advantages offered by such system are

documentation of knowledge, intelligent decision support, self learning, reasoning and explanation.

Knowledge-based systems[1]

are systems based on the methods and techniques ofArtificialIntelligence. Their core components are:

y knowledge basey acquisition mechanismsy inference mechanisms

1.1 What is a Knowledge-Based System?

Knowledge-Based Systems are one branch of Artificial Intelligence, and we can say they are a

reality in the systems development world nowadays. They are usually embedded in otherapplications, performing knowledge-specialized tasks.


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Knowledge-Based Systems are the result of a long investigation process performed by ArtificialIntelligence scientists. In the early 70's, they started to understand that the capabilities of a

computer program to solve problems are neither the formal expression nor the inference logicschemes but the knowledge it has. An expert is a person who owns a type of knowledge and

experience in some human field activity, and he can apply it efficiently in solving different tasks

that he does not know specifically, but are in his knowledge domain. Therefore, aK

nowledge-Based System is a group of computer programs that tries to emulate, and even outdo in somesituations, a human expert in his field. The idea is not to replace human thinking by a machine,

just the expertise of a competent professional. In order to build a KBS, Knowledge Engineers areusually advised by these experts. In some fields, these experts work using rules, although they do

not always realize it.

Knowledge-Based Systems are powerful when it is not necessary to use either intuition orcommon sense, getting successful results.

There have been two generations in Knowledge-Based Systems. In the first one, Knowledge

Engineers were limited to code rules containing the knowledge of an expert. This formalism wasnot good enough because the projects were very difficult to maintain and expensive. Besides this,

knowledge acquisition was heavily dependent on the expert. In the second generation, AllenNewel proposed the Knowledge Level, where knowledge is independent of implementation and

it is structured according to the different knowledge levels:

y Knowledge level: Agent, knowledge, goal, actionsy Symbolic level: Computer, symbols, instructionsy Logic level: Digital system, bits, logic and arithmetic operationsy Circuit level: Electronic system, current

Newell points out the need to use models. In this way, we define "knowledge acquisition" as aprocess where the Knowledge Engineer creates a knowledge model that he will later make

computational

1.3 Where are They Used?

y Support system decision-making: Starting from a given problem, these systemsdetermine the most adequate solution according to the system-included knowledge.

y Configuration: They select and plan the required components needed in a particularprocess. For example, systems that help to configure physical equipment, starting

from the given components and requirements.

y Diagnosis: These systems determine the causes of a symptom, for example,disease diagnosis and troubleshooting.

y Interpretation and analysis: They deal with large amounts of information,interpreting it, giving an explicative report and suggesting actions to take. An

example of this is systems to evaluate resistance of structures against earthquakes.

y Monitoring: It's a particular case of interpretation and analysis that is veryfrequently used, so it will be considered separately. Its purpose is usually monitoring


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a process and giving a control output, for example, the control of a nuclear power

plant.

y Planning: They establish the stages and resources to get a goal. Examples of thisare systems to solve industrial logistic problems.

y Intelligence interfaces: They solve situations where complex equipment is difficultto use by people, for example, an autopilot.

y Design: Advice in Computer Aided Design (CAD), for example, the correct voltage inan electronic design program.

Knowledge Base

A KBS has the human expert knowledge in a formalized and structured form; this is what is

known as a knowledge base. Some Knowledge-Based Systems include metaknowledge orknowledge about knowledge, that is to say, the capability to search the knowledge base and findthe solution of a problem in an intelligent manner, using different resolution strategies with their

particular conditions. This means that some criteria are defined, by which the system decides oneor the other strategy in function of initial data. The knowledge base can be represented as

predicate calculus, lists, objects, semantic networks, and/or production rules. Most frequently, itis implemented using rules and objects.

Inference Engine

It is also called rule interpreter, and its goal is to search and select the correct rule to be applied

in the reasoning process.

Facts Base

It is like a temporal-auxiliary memory that stores the user data, initial problem data, hypothesis,

and intermediate results during the inference process. Through it, we can know the current

system status and how it was reached. The best way to store this information is in relationaldatabases, rather than in other rudimentary systems.


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UserInterface

It allows communicating with the KBS, data input and output.

knowledge base system

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