application2
expert system
what is expert system ?
· an expert system is a computer program that simulates the thought process of a human expert to solve complex decision problems in a specific domain.
the need for expert systems
expert systems are necessitated by the limitations associated with conventional human decision-making processes, including:
benefits of expert systems
expert systems offer an environment where the good capabilities of humans and the power of computers can be incorporated to overcome many of the limitations discussed in the previous section.
applications of expert system
expert system characteristics
? operates as an interactive system
? tools have ability to sift (filter) knowledge.
? make logical inferences based on knowledge stored
?ability to explain reasoning
? domain-specific
? capability to assign confidence values
? cost-effective alternative to human expert
expert system architecture
l the user interacts with the system through a
l user interface which may use menus, natural language or any other style of interaction).
l the core components of expert systems are the knowledge base and the reasoning engine.
l then an inference engine is used to reason with both the expert knowledge (extracted from our friendly expert) and data specific to the particular problem being solved. the expert knowledge will typically be in the form of a set of if-then rules.
l the case specific data includes both data provided by the user and partial conclusions (along with certainty measures) based on this data.
l almost all expert systems also have an explanation subsystem, which allows the program to explain its reasoning to the user. some systems also have a
l knowledge base editor which help the expert or knowledge engineer to easily updating and check the knowledge base.
l one important feature of expert systems is the way they (usually) separate domain specific knowledge from more general purpose reasoning and representation techniques.
l the general purpose bit (in the dotted box in the figure) is referred to as an expert system shell. as we see in the figure, the shell will provide the inference engine (and knowledge representation scheme), a user interface, an explanation system and sometimes a knowledge base editor.
l using shells to write expert systems generally greatly reduces the cost and time of development.
knowledge acquisition
l knowledge acquisition is transferring knowledge from human expert to computer. knowledge acquisition includes the elicitation, collection, analysis, modeling and validation of knowledge.
issues in knowledge acquisition
?knowledge representation
rules as a knowledge representation technique
the main players in the development team
· there are five members of the expert system development team: the domain expert, the knowledge engineer, the programmer, the project manager and the end-user.
structure of a rule-based expert system
basic structure of a rule-based expert system
inference engine
forward chaining algorithm.
backward chaining algorithm.
the explanation
· a unique feature of an expert system is its explanation capability. it enables the expert system to review its own reasoning and explain its decisions.
l types of explanation
user interface
can expert systems make mistakes?
how do we choose between forward and backward chaining?
advantages of rule-based expert systems
· natural knowledge representation.
· uniform structure.
· separation of knowledge from its processing.
· dealing with incomplete and uncertain knowledge
المادة المعروضة اعلاه هي مدخل الى المحاضرة المرفوعة بواسطة استاذ(ة) المادة . وقد تبدو لك غير متكاملة . حيث يضع استاذ المادة في بعض الاحيان فقط الجزء الاول من المحاضرة من اجل الاطلاع على ما ستقوم بتحميله لاحقا . في نظام التعليم الالكتروني نوفر هذه الخدمة لكي نبقيك على اطلاع حول محتوى الملف الذي ستقوم بتحميله .