Which expert system operating mode allows determining if a given hypothesis is valid?
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A. B. C. D.D.
Backward-chaining mode - the expert system backtracks to determine if a given hypothesis is valid.
Backward-chaining is generally used when there are a large number of possible solutions relative to the number of inputs.
Incorrect answers are: In a forward-chaining mode, the expert system acquires information and comes to a conclusion based on that information.
Forward-chaining is the reasoning approach that can be used when there is a small number of solutions relative to the number of inputs.
Blackboard is an expert system-reasoning methodology in which a solution is generated by the use of a virtual blackboard, wherein information or potential solutions are placed on the blackboard by a plurality of individuals or expert knowledge sources.
As more information is placed on the blackboard in an iterative process, a solution is generated.
Lateral-chaining mode - No such expert system mode.
Sources: KRUTZ, Ronald L.
& VINES, Russel.
D., The CISSP Prep Guide: Mastering the Ten Domains of Computer Security, John Wiley & Sons, 2001, Chapter 7: Applications and Systems Development (page 259)
KRUTZ, Ronald & VINES, Russel, The CISSP Prep Guide: Gold Edition, Wiley Publishing Inc., 2003, Chapter 7: Expert Systems (page 354).
The expert system is a computer program that uses artificial intelligence (AI) technologies to mimic the decision-making ability of a human expert in a particular domain. Expert systems are typically used to solve complex problems in various fields, including medicine, finance, engineering, and security.
Expert systems use various modes of operation to make inferences and reach conclusions based on input data and pre-existing knowledge. One such mode is called backward chaining.
Backward chaining is a problem-solving method used by expert systems to determine the validity of a given hypothesis or conclusion by working backward from the goal. In backward chaining, the expert system starts with a given conclusion or hypothesis and works backward through a set of rules or facts to determine whether the hypothesis is true or false.
To use backward chaining, the expert system starts with a given hypothesis and checks if there are any facts or rules that can support or contradict the hypothesis. If there are any supporting facts or rules, the system continues to work backward until it reaches a set of initial conditions or a known fact. If the expert system can find a set of facts or rules that support the given hypothesis, it concludes that the hypothesis is valid.
In contrast, forward chaining is another problem-solving method used by expert systems. In forward chaining, the system starts with a set of initial conditions and works forward through a set of rules to reach a conclusion. Forward chaining is typically used in situations where the goal is to find a solution to a problem rather than to determine the validity of a given hypothesis.
Lateral chaining and blackboard are two other modes of operation used by expert systems. Lateral chaining is a problem-solving method that involves exploring different alternatives or hypotheses simultaneously. Blackboard is a mode of operation that allows multiple expert systems to work together on a problem by sharing knowledge and results on a common "blackboard" platform.
In summary, the expert system operating mode that allows determining if a given hypothesis is valid is backward chaining.