KNOWLEDGE BASED SYSTEMS 01

Goal :

Try to solve the kinds of difficult problems that normally require human experts by using computer based information system & to construct computer programs that perform at high levels of competence in cognitive tasks.

Definition :

Knowledge based systems are Software that uses artificial intelligent or expert system 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, it focuses on systems that use knowledge-based techniques to support human decision-making, learning and action. It incorporates a store (database) of expert knowledge with couplings and linkage designed to facilitate its retrieval in response to specific queries, or to transfer expertise from one domain of knowledge to another. 

Knowledge-Based Systems 

Knowledge-Based systems are capable of cooperating with human users and so the quality of support given and the manner. Knowledge-based systems are systems based on the methods and techniques of Artificial Intelligence in problem solving processes. Their core components are:

• Knowledge Base                                              
• Acquisition Mechanisms
• Inference Mechanisms

Building, validating, and maintaining a knowledge base is a skill (art) called knowledge engineering. The basic advantages offered by such system are documentation of knowledge, intelligent decision support, self-learning, reasoning and explanation.

Knowledge based system’s Characteristics 

·         Symbolic: It incorporates knowledge that is symbolic (as well as numeric).

·         Heuristic: It reasons with judgmental, imprecise, and qualitative knowledge as well as with formal knowledge of established theories.

·       Transparent: Its knowledge is simply and explicitly represented in terms familiar to specialists, and is separate from its inference procedures. It provides explanations of its line of reasoning and answers to queries about its knowledge.

·      Flexible: It is incrementally refinable and extensible. More details can be specified to refine its performance, more concepts and links among concepts can be specified to broaden its range of applicability.

The Reasoning Mechanism 

·         Takes descriptions from the user about the problem to be solved.

·         Requests additional information from the user as needed.

·         Interprets the knowledge base to make inferences, draw conclusions, and ultimately give advice.

·         Explains its reasoning to the user (how were the conclusions reached?)

Knowledge-Based Systems Limitations

·                               Knowledge-based generation and maintenance are difficult chores.

·                              Knowledge-based systems "know" only the things in the knowledge base.

·                             They do not know how their rules were developed.

·                             They do not know when to break their own rules.

·                             They do not look at problems from different perspectives.

·                            They typically cannot learn from their own experiences.