Expert Systems Questions and Answers

Q: Which characteristic distinguishes an expert system from conventional software?

Conventional programs interleave knowledge and control in procedural code, while an expert system keeps the domain knowledge declarative and lets a general engine apply it. That separation is what enables explanation, incremental authoring and shell reuse. Language choice is incidental, speed is usually worse, and validation guarantees nothing of the kind. Every other characteristic of these systems follows from this one. The quantity that varies and the quantity that does not are worth naming before any substitution is attempted.

Q: Which property allows an expert system to be extended incrementally?

Because a rule states a relation rather than a step in a procedure, adding one does not require rewriting anything else, which is what let knowledge bases grow through use. Recompilation, implementation language and regression testing are engineering practices rather than the enabling property. The qualification is that interaction through working memory erodes the independence as the base grows. A single measurement chosen to respond to the one asymmetry beats several that respond to shared behaviour.

Q: Which representation suits knowledge stated as a small fixed set of conditions and actions?

A decision table lists every combination of a few conditions against the action each requires, which is compact, easy to check for completeness and easy to convert into rules. Frames, networks and blackboards address structure, relations and cooperation. The table's chief virtue is that missing and contradictory combinations are visible at a glance, which is exactly what verification of a rule base struggles to achieve. Framing the question as which quantity the change acts upon makes the answer follow without calculation.

Q: Which advantage does a decision table have over an equivalent rule set?

Every combination of conditions appears as a column, so a gap or a contradiction is immediately visible, whereas the same defect hides easily in a list of rules. Expressive power is lower rather than higher, speed is comparable and evaluation order is not the point. Tables are therefore often used as the authoring medium and compiled into rules for execution.

Q: Which term describes a set of rules that leads back to its own starting condition?

Circular rules can drive an engine into an unterminating loop, or at best waste effort rederiving what is already known. Refractoriness limits the damage but does not remove the defect. Subsumption, redundancy and unreachability are the other three classical faults that static verification looks for. Detecting circularity amounts to finding a cycle in the graph of rule dependencies.

Q: Which structure does forward chaining most naturally build?

Forward chaining keeps asserting conclusions into working memory until the rules are exhausted, so what accumulates is a set of derived facts. The goal-rooted proof tree belongs to backward chaining, frontiers to search and dependency networks to truth maintenance. Because everything derivable is derived, forward chaining can do a great deal of irrelevant work when only one conclusion was wanted. Reading the definition literally, rather than recalling a formula, is the reliable route through questions of this shape.

Q: Which inefficiency is characteristic of forward chaining?

Data-driven inference pursues every consequence of the facts, so in a large base most of the work has nothing to do with the question of interest. Redundant questioning and repeated subgoals are backward-chaining faults, and duplicated knowledge bases belong to nothing here. Goal-directed filtering, or a hybrid regime, is the usual remedy when a forward system must answer specific queries. Naming the cost of a choice alongside its benefit is what turns a fact into a design decision. Checking the units of each quantity catches a wrong formula before the arithmetic begins.

Q: What does a goal-driven engine waste effort on most often?

A subgoal needed by several rules is proved afresh each time unless the engine caches results, which is why memoisation matters in goal-directed systems. Irrelevant derivation and exhaustive matching are forward-chaining costs, the latter addressed by Rete. Recognising that the two regimes fail in opposite ways is what guides the choice, and hybrid engines exist precisely to get both benefits.

Q: Which regime do many practical shells actually use?

Real systems commonly chain forward from newly supplied data to derive cheap consequences, then chain backward to test the hypotheses that survive. The mixture keeps both the irrelevant derivation and the repeated questioning within bounds. Committing to one direction is a textbook simplification. Knowing that the choice is a spectrum rather than a dichotomy is the practical point.

Q: Assertion (A): An expert system can explain its reasoning to a user. Reason (R): Its domain knowledge is represented declaratively and the trace of fired rules is available. Select the correct answer from the options below.

Explanation is possible precisely because the knowledge is stored as inspectable rules rather than compiled into procedural code, so the sequence of rules that fired can be replayed as a justification. A conventional program has no comparable record. This is the clearest practical dividend of the separation of knowledge from control, and it was decisive in gaining user acceptance for MYCIN and its successors.

61.

Which characteristic distinguishes an expert system from conventional software?

A.It always runs faster
B.It cannot produce an incorrect answer once the knowledge base has been properly validated
C.Knowledge is separated from the control that uses it
D.It is written in a specialised language that only a knowledge engineer is able to read easily

Answer: C

Conventional programs interleave knowledge and control in procedural code, while an expert system keeps the domain knowledge declarative and lets a general engine apply it. That separation is what enables explanation, incremental authoring and shell reuse. Language choice is incidental, speed is usually worse, and validation guarantees nothing of the kind. Every other characteristic of these systems follows from this one. The quantity that varies and the quantity that does not are worth naming before any substitution is attempted.

Discuss in Forum

62.

Which property allows an expert system to be extended incrementally?

A.The inference engine recompiles the whole knowledge base whenever any rule has been changed
B.The shell is written in C
C.Each new rule is tested against the complete set of stored cases before it is finally accepted
D.Rules are declarative and independent

Answer: D

Because a rule states a relation rather than a step in a procedure, adding one does not require rewriting anything else, which is what let knowledge bases grow through use. Recompilation, implementation language and regression testing are engineering practices rather than the enabling property. The qualification is that interaction through working memory erodes the independence as the base grows. A single measurement chosen to respond to the one asymmetry beats several that respond to shared behaviour.

Discuss in Forum

63.

Which representation suits knowledge stated as a small fixed set of conditions and actions?

A.A decision table
B.A frame hierarchy, in which specific concepts inherit the slots defined on general concepts
C.A semantic network
D.A blackboard, on which several independent knowledge sources contribute to a shared solution

Answer: A

A decision table lists every combination of a few conditions against the action each requires, which is compact, easy to check for completeness and easy to convert into rules. Frames, networks and blackboards address structure, relations and cooperation. The table's chief virtue is that missing and contradictory combinations are visible at a glance, which is exactly what verification of a rule base struggles to achieve. Framing the question as which quantity the change acts upon makes the answer follow without calculation.

Discuss in Forum

64.

Which advantage does a decision table have over an equivalent rule set?

A.It allows the conditions to be evaluated in any order the inference engine happens to choose
B.Completeness is easy to check
C.It can express relations between objects that a set of production rules would be unable to state
D.It executes faster

Answer: B

Every combination of conditions appears as a column, so a gap or a contradiction is immediately visible, whereas the same defect hides easily in a list of rules. Expressive power is lower rather than higher, speed is comparable and evaluation order is not the point. Tables are therefore often used as the authoring medium and compiled into rules for execution.

Discuss in Forum

65.

Which term describes a set of rules that leads back to its own starting condition?

A.Redundancy
B.Unreachability, in which no combination of facts can ever satisfy a given rule's conditions
C.Circularity
D.Subsumption, in which the conditions of one rule are implied by the conditions of another

Answer: C

Circular rules can drive an engine into an unterminating loop, or at best waste effort rederiving what is already known. Refractoriness limits the damage but does not remove the defect. Subsumption, redundancy and unreachability are the other three classical faults that static verification looks for. Detecting circularity amounts to finding a cycle in the graph of rule dependencies.

Discuss in Forum

66.

Which structure does forward chaining most naturally build?

A.A proof tree rooted at the goal and branching down towards the facts the user has supplied
B.A search frontier
C.A dependency network recording which of the beliefs currently held support which other beliefs
D.A growing set of derived facts

Answer: D

Forward chaining keeps asserting conclusions into working memory until the rules are exhausted, so what accumulates is a set of derived facts. The goal-rooted proof tree belongs to backward chaining, frontiers to search and dependency networks to truth maintenance. Because everything derivable is derived, forward chaining can do a great deal of irrelevant work when only one conclusion was wanted. Reading the definition literally, rather than recalling a formula, is the reliable route through questions of this shape.

Discuss in Forum

67.

Which inefficiency is characteristic of forward chaining?

A.Deriving conclusions nobody asked for
B.Asking the user for information that the system could have derived from what it already knows
C.Re-proving the same subgoal
D.Storing a separate copy of the knowledge base for each hypothesis being considered in parallel

Answer: A

Data-driven inference pursues every consequence of the facts, so in a large base most of the work has nothing to do with the question of interest. Redundant questioning and repeated subgoals are backward-chaining faults, and duplicated knowledge bases belong to nothing here. Goal-directed filtering, or a hybrid regime, is the usual remedy when a forward system must answer specific queries. Naming the cost of a choice alongside its benefit is what turns a fact into a design decision. Checking the units of each quantity catches a wrong formula before the arithmetic begins.

Discuss in Forum

68.

What does a goal-driven engine waste effort on most often?

A.Requiring the whole of working memory to be re-examined after every single assertion is made
B.Re-establishing the same subgoal repeatedly
C.Deriving a large number of conclusions that turn out to be irrelevant to the question asked
D.Matching every rule each cycle

Answer: B

A subgoal needed by several rules is proved afresh each time unless the engine caches results, which is why memoisation matters in goal-directed systems. Irrelevant derivation and exhaustive matching are forward-chaining costs, the latter addressed by Rete. Recognising that the two regimes fail in opposite ways is what guides the choice, and hybrid engines exist precisely to get both benefits.

Discuss in Forum

69.

Which regime do many practical shells actually use?

A.Backward chaining only
B.Neither, since a modern shell relies on constraint propagation rather than on chaining at all
C.A mixture of both directions
D.Forward chaining only, since it is the simpler of the two to implement in a production system

Answer: C

Real systems commonly chain forward from newly supplied data to derive cheap consequences, then chain backward to test the hypotheses that survive. The mixture keeps both the irrelevant derivation and the repeated questioning within bounds. Committing to one direction is a textbook simplification. Knowing that the choice is a spectrum rather than a dichotomy is the practical point.

Discuss in Forum

70.

Assertion (A): An expert system can explain its reasoning to a user.

Reason (R): Its domain knowledge is represented declaratively and the trace of fired rules is available.

Select the correct answer from the options below.

A.Both A and R are true, but R is not the correct explanation of A
B.A is true but R is false
C.A is false but R is true
D.Both A and R are true, and R is the correct explanation of A

Answer: D

Explanation is possible precisely because the knowledge is stored as inspectable rules rather than compiled into procedural code, so the sequence of rules that fired can be replayed as a justification. A conventional program has no comparable record. This is the clearest practical dividend of the separation of knowledge from control, and it was decisive in gaining user acceptance for MYCIN and its successors.

Discuss in Forum

Loading…

Topics

Other Subjects

Tags: Expert Systems Questions and Answers || Expert Systems MCQ Questions and Answers || Expert Systems GK Questions and Answers || Expert Systems GK MCQ Questions || Expert Systems Multiple Choice Questions and Answers || Expert Systems GK || GK on Expert Systems || Artificial Intelligence Questions and Answers || Artificial Intelligence MCQ Questions and Answers || Artificial Intelligence GK Questions and Answers || GK on Artificial Intelligence

Expert Systems Questions and Answers

Topics

Other Subjects

About Us

Stay informed about all important Dates & Notifications