Expert Systems Questions and Answers

Q: Which reasoning direction starts from the known facts?

Forward chaining is data-driven: it fires whatever rules the current facts enable and keeps going until nothing more can be concluded. It suits monitoring and configuration, where the data arrive first and the goal is unknown. Backward chaining works the other way, and abduction and means-ends analysis are different strategies again. Matching the direction to the shape of the task is the first design decision in building any rule-based system.

Q: Which reasoning direction starts from a goal?

Backward chaining takes a hypothesis, finds the rules that would conclude it and tries to establish their conditions in turn, asking the user when nothing else will settle them. It suits diagnosis, where the candidate conclusions are few and known in advance. Forward chaining, search order and conflict resolution are separate notions. The characteristic question-asking style of a diagnostic consultation falls directly out of this control regime.

Q: Which task type favours forward chaining?

When data arrive continuously and any of many conclusions might follow, running rules forward from the data is natural, which is why process control and configuration systems chain forward. A short candidate list instead favours backward chaining, since each hypothesis can be tested cheaply. Single readings and yes-or-no queries are goal-directed. The rule of thumb is that few facts and many goals chain backward, many facts and few goals chain forward.

Q: Which mechanism selects among rules that are all eligible?

Conflict resolution picks one rule from the conflict set using strategies such as recency, specificity, priority or refractoriness. Matching produces the set; resolution chooses within it. Truth maintenance handles retraction and acquisition handles authoring. Because the choice can change which conclusion is reached, the strategy is part of the system's semantics and not merely an efficiency device. A limit that survives making every external component ideal is an intrinsic one, and worth knowing for that reason.

Q: Which conflict resolution strategy prefers the most recent facts?

Recency fires the rule matching the most recently asserted working-memory element, which keeps attention on the current line of reasoning rather than wandering. Specificity prefers the more detailed rule, refractoriness stops a rule firing twice on the same data, and explicit priorities are set by hand. Most engines combine several of these in a fixed order, so knowing what each contributes is needed to predict behaviour. Working one numerical case through both cases side by side fixes the distinction better than any rule of thumb.

Q: Which strategy stops a rule firing repeatedly on the same data?

Refractoriness removes an instantiation from the conflict set once it has fired, so the same rule with the same bindings cannot loop forever. Without it, a rule whose action does not change its own conditions would fire endlessly. Recency, specificity and file order address different questions. It is the least visible of the strategies and the one whose absence is noticed immediately.

Q: Which algorithm makes rule matching efficient in large systems?

Rete compiles the rule conditions into a network that stores partial matches, so only the consequences of a change are recomputed rather than every rule being retested. It trades memory for speed and made large production systems practical. A star, unification and resolution belong to search and to logical inference. The insight that working memory changes slowly between cycles is what the whole design exploits. Working one numerical case through both cases side by side fixes the distinction better than any rule of thumb.

Q: Which property of working memory does Rete exploit?

Temporal redundancy means most facts survive from one cycle to the next, so rebuilding every match from scratch repeats almost all of the previous work. Rete stores the partial matches and updates them incrementally. Relative sizes, sort order and confirmation status are not what the algorithm depends on. Naming the property rather than the network is what lets you predict when Rete will and will not help. The quantity that varies and the quantity that does not are worth naming before any substitution is attempted.

Q: Which representation groups an object's properties into named slots?

A frame collects the attributes of a concept as slots, each able to carry a value, a default, a type restriction or an attached procedure. Frames support inheritance along an is-a hierarchy, which rules do not. Decision tables and certainty factors serve different purposes entirely. Frames and rules are usually combined rather than opposed, with frames holding the objects and rules holding the reasoning about them. A single measurement chosen to respond to the one asymmetry beats several that respond to shared behaviour.

Q: Which frame feature supplies a value when none has been given?

A default fills the slot with a typical value that later evidence may override, which is how frames express stereotypes economically. Demons are attached procedures, facets are the sub-fields describing a slot, and inheritance is the mechanism by which a default is often obtained. The ability to override a default is what makes frame reasoning non-monotonic in the same way that human expectations are. A single measurement chosen to respond to the one asymmetry beats several that respond to shared behaviour.

11.

Which reasoning direction starts from the known facts?

A.Forward chaining
B.Backward chaining, which begins with a hypothesis and looks for evidence supporting it
C.Abductive reasoning
D.Means-ends analysis, which repeatedly reduces the difference between two states

Answer: A

Forward chaining is data-driven: it fires whatever rules the current facts enable and keeps going until nothing more can be concluded. It suits monitoring and configuration, where the data arrive first and the goal is unknown. Backward chaining works the other way, and abduction and means-ends analysis are different strategies again. Matching the direction to the shape of the task is the first design decision in building any rule-based system.

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12.

Which reasoning direction starts from a goal?

A.Conflict resolution, which chooses among the rules that are eligible to fire
B.Backward chaining
C.Forward chaining, which fires every rule whose conditions the current facts already satisfy
D.Breadth-first search

Answer: B

Backward chaining takes a hypothesis, finds the rules that would conclude it and tries to establish their conditions in turn, asking the user when nothing else will settle them. It suits diagnosis, where the candidate conclusions are few and known in advance. Forward chaining, search order and conflict resolution are separate notions. The characteristic question-asking style of a diagnostic consultation falls directly out of this control regime.

Discuss in Forum

13.

Which task type favours forward chaining?

A.Interpreting a single reading
B.Answering a specific yes or no question posed by the user at the outset
C.Monitoring a stream of incoming data
D.Diagnosing a fault when a short list of candidate causes is already known

Answer: C

When data arrive continuously and any of many conclusions might follow, running rules forward from the data is natural, which is why process control and configuration systems chain forward. A short candidate list instead favours backward chaining, since each hypothesis can be tested cheaply. Single readings and yes-or-no queries are goal-directed. The rule of thumb is that few facts and many goals chain backward, many facts and few goals chain forward.

Discuss in Forum

14.

Which mechanism selects among rules that are all eligible?

A.Pattern matching, which determines which rules have their conditions satisfied at all
B.Truth maintenance
C.Knowledge acquisition, which decides which new rules should be added to the base
D.Conflict resolution

Answer: D

Conflict resolution picks one rule from the conflict set using strategies such as recency, specificity, priority or refractoriness. Matching produces the set; resolution chooses within it. Truth maintenance handles retraction and acquisition handles authoring. Because the choice can change which conclusion is reached, the strategy is part of the system's semantics and not merely an efficiency device. A limit that survives making every external component ideal is an intrinsic one, and worth knowing for that reason.

Discuss in Forum

15.

Which conflict resolution strategy prefers the most recent facts?

A.Recency
B.Specificity, which prefers the rule whose condition part imposes the most constraints
C.Refractoriness
D.Priority ordering, in which the knowledge engineer assigns each rule an explicit rank

Answer: A

Recency fires the rule matching the most recently asserted working-memory element, which keeps attention on the current line of reasoning rather than wandering. Specificity prefers the more detailed rule, refractoriness stops a rule firing twice on the same data, and explicit priorities are set by hand. Most engines combine several of these in a fixed order, so knowing what each contributes is needed to predict behaviour. Working one numerical case through both cases side by side fixes the distinction better than any rule of thumb.

Discuss in Forum

16.

Which strategy stops a rule firing repeatedly on the same data?

A.Depth-first ordering, in which the rule appearing earliest in the file is always chosen
B.Refractoriness
C.Recency, which prefers whichever rule matches the most recently asserted element in memory
D.Specificity

Answer: B

Refractoriness removes an instantiation from the conflict set once it has fired, so the same rule with the same bindings cannot loop forever. Without it, a rule whose action does not change its own conditions would fire endlessly. Recency, specificity and file order address different questions. It is the least visible of the strategies and the one whose absence is noticed immediately.

Discuss in Forum

17.

Which algorithm makes rule matching efficient in large systems?

A.Unification
B.Resolution refutation, which proves a goal by deriving a contradiction from its negation
C.The Rete algorithm
D.The A star algorithm, which searches a graph guided by an admissible heuristic estimate

Answer: C

Rete compiles the rule conditions into a network that stores partial matches, so only the consequences of a change are recomputed rather than every rule being retested. It trades memory for speed and made large production systems practical. A star, unification and resolution belong to search and to logical inference. The insight that working memory changes slowly between cycles is what the whole design exploits. Working one numerical case through both cases side by side fixes the distinction better than any rule of thumb.

Discuss in Forum

18.

Which property of working memory does Rete exploit?

A.It contains far fewer facts than the knowledge base contains rules in a typical system
B.It is stored in sorted order
C.It holds only assertions that have already been confirmed by the user of the system
D.It changes only slightly between cycles

Answer: D

Temporal redundancy means most facts survive from one cycle to the next, so rebuilding every match from scratch repeats almost all of the previous work. Rete stores the partial matches and updates them incrementally. Relative sizes, sort order and confirmation status are not what the algorithm depends on. Naming the property rather than the network is what lets you predict when Rete will and will not help. The quantity that varies and the quantity that does not are worth naming before any substitution is attempted.

Discuss in Forum

19.

Which representation groups an object's properties into named slots?

A.A frame
B.A production rule, whose condition part lists the properties that must hold together
C.A decision table
D.A certainty factor, which records how strongly a conclusion follows from its evidence

Answer: A

A frame collects the attributes of a concept as slots, each able to carry a value, a default, a type restriction or an attached procedure. Frames support inheritance along an is-a hierarchy, which rules do not. Decision tables and certainty factors serve different purposes entirely. Frames and rules are usually combined rather than opposed, with frames holding the objects and rules holding the reasoning about them. A single measurement chosen to respond to the one asymmetry beats several that respond to shared behaviour.

Discuss in Forum

20.

Which frame feature supplies a value when none has been given?

A.An inheritance link, which connects a specific frame to the more general frame above it
B.A default
C.A demon, which is a procedure that runs whenever the slot's value is read or written
D.A facet

Answer: B

A default fills the slot with a typical value that later evidence may override, which is how frames express stereotypes economically. Demons are attached procedures, facets are the sub-fields describing a slot, and inheritance is the mechanism by which a default is often obtained. The ability to override a default is what makes frame reasoning non-monotonic in the same way that human expectations are. A single measurement chosen to respond to the one asymmetry beats several that respond to shared behaviour.

Discuss in Forum

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