Expert Systems Flashcards
what are expert systems?
its a knowledge based systems, that is an application of artificial intelligence. an expert system is almost always used in narrow field of knowledge
what is the field of knowledge called?
the knowledge domain of the system
what are the key components of expert systems?
to create an expert system a subject experts team of programmers and technical experts are required
expert system is an experienced practitioner in particular field e.g. medical specialist
the initial stage of building the expert system is known as knowledge acquisition
knowledge of human expert is programmed and represented as rules and facts- result is the creation of knowledge basis. it can be stored as a series of IF-THEN-ELSE rules
what are the two types of knowledge bases in expert systems?
factual
heuristic
what is factual knowledge?
factual information acquired by the knowledge engineers from human experts, relating to subject domain- this information would be widely agreed
what is heuristic knowledge?
captures information about accurate judgement and ability to estimate and evaluate. such rules are not derived from logic alone but from personal experience- described as rule of thumb.
designed to work with uncertainty and stimulate producing decisions based on experience
what is the name of the consulting system put in place after knowledge base has been created?
inference engine
the software interrogates the knowledge base and draws inferences and conclusions based on rules stored about subject domain
it poses questions to user and uses answers provided by user to determine suitable response
what is a user interface?
it allows a user to communicate with the system. requests for information or advice are passed from the user interface to interface engine. the request is processed by inference engine which applies rules to the knowledge base and returns a response to the user
what is a shell?
its a piece of software which contains the structure for creating an expert system. it is described as an empty system without knowledge base
, the creator can enter appropriate rules and facts to generate an expert system
applications of fuzzy logic
lower-level machine control, especially consumer products
fuzzy logic is integrated into home appliances such as- vacuum cleaner, microwave ovens and video cameras
e.g. anti-lock brake system in a car
the control rules contains parameters such as brake pressure and break temperature
what are the examples expert systems?
medicine
care engine fault diagnosis
life insurance
medicine expert system enable situations where:
they have to decide who gets treated first
GP knowledge may be out of date or may not be aware of new modern drug
may not be aware of new rare condition and therefore don’t recognise it or how to deal with it
they may be unsure of diagnosis and want to check diagnosis with someone with more experience
how would the medicine expert system work?
the knowledge base would contain medical information, the patients symptoms would be used as the query and the advice would be diagnosis of the patients illness
how would the car fault manufacturer expert system work?
the information is stored on a computer which can be plugged into the car to determine the nature of the fault. the system will recommend how to fix the problem
what are the factors when calculating insurance prices
age
gender
smoking status
health
how does life insurance expert system work?
the system will present questions to the user based on their responses, through the use of inference engine, interrogate the knowledge base to produce a cost for the premium based on the individual response of the user
human experts in the form of consultants are required. the consultants will be questioned by the knowledge engineers. they explain how they make the decisions about life insurance applications with information/data or rule of thumb
benefits of using expert system
expert advice is always available
knowledge of experts can be recorded and used before they move on
can be used as a training aid to increase the expertise of staff
makes rational decisions without emotional overhead
doesn’t get tired
can perform tasks much faster than human experts
can quickly identify faults in equipment
very accurate
more cheaper
expert system can be harnessed with combination of lots of experts- one expert shared globally
limitations of using expert system
can make mistakes and don’t learn from them
risk is over reliance on technology- may become deskilled
work well when problems are specific and well defined. less suited to less predictable decisions
human advisor may take into account special circumstances which would be overlooked
can give its reasons for a decision- but cannot be questioned further
every scenario cannot be programmed- errors may be possible
what is the structure of expert system?
knowledge acquisition> knowledge base> inference engine>
user interface>use
