Q#1: Knowledge representation in AI is used to:
(A) Store and use information about the world
(B) Randomly explore states
(C) Expand BFS only
(D) DFS depth control
Answer: (A) Store and use information about the world
Q#2: Declarative knowledge expresses:
(A) Facts about the world
(B) Actions only
(C) Random moves
(D) Heuristics
Answer: (A) Facts about the world
Q#3: Procedural knowledge expresses:
(A) How to do things
(B) Facts only
(C) BFS nodes
(D) DFS depth
Answer: (A) How to do things
Q#4: A knowledge base consists of:
(A) Facts and rules
(B) Random values
(C) BFS tree
(D) DFS depth only
Answer: (A) Facts and rules
Q#5: A fact in knowledge representation is:
(A) A statement that is true about the world
(B) An action
(C) A heuristic
(D) A variable
Answer: (A) A statement that is true about the world
Q#6: A rule represents:
(A) Conditional knowledge
(B) Random choice
(C) BFS node
(D) DFS depth
Answer: (A) Conditional knowledge
Q#7: In logic-based representation, knowledge is expressed in:
(A) Formal logic
(B) Natural language
(C) Random symbols
(D) BFS nodes
Answer: (A) Formal logic
Q#8: First-order logic allows:
(A) Quantifiers like ∀ and ∃
(B) Only propositional statements
(C) Random search
(D) BFS expansion
Answer: (A) Quantifiers like ∀ and ∃
Q#9: A predicate in logic represents:
(A) Property or relation
(B) Variable only
(C) BFS node
(D) Random value
Answer: (A) Property or relation
Q#10: Inference in AI is:
(A) Deriving new facts from known facts
(B) Random assignment
(C) BFS expansion
(D) DFS depth control
Answer: (A) Deriving new facts from known facts
Q#11: Forward chaining is:
(A) Data-driven inference
(B) Goal-driven inference
(C) BFS only
(D) DFS only
Answer: (A) Data-driven inference
Q#12: Backward chaining is:
(A) Goal-driven inference
(B) Data-driven inference
(C) BFS only
(D) DFS only
Answer: (A) Goal-driven inference
Q#13: Semantic networks represent knowledge as:
(A) Graphs of nodes and edges
(B) Trees only
(C) BFS nodes
(D) Random variables
Answer: (A) Graphs of nodes and edges
Q#14: Nodes in semantic networks represent:
(A) Concepts or objects
(B) Values only
(C) Actions
(D) BFS nodes
Answer: (A) Concepts or objects
Q#15: Edges in semantic networks represent:
(A) Relations between nodes
(B) Values only
(C) Actions
(D) DFS depth
Answer: (A) Relations between nodes
Q#16: Frames are used to represent:
(A) Structured knowledge about objects
(B) Random assignments
(C) BFS nodes
(D) DFS depth
Answer: (A) Structured knowledge about objects
Q#17: Slots in a frame represent:
(A) Attributes of the object
(B) Nodes only
(C) Edges only
(D) BFS expansion
Answer: (A) Attributes of the object
Q#18: Default values in frames are used to:
(A) Represent typical properties
(B) BFS nodes
(C) DFS depth
(D) Random values
Answer: (A) Represent typical properties
Q#19: Inheritance in frames allows:
(A) Subclasses to inherit properties from parent classes
(B) Random values
(C) BFS only
(D) DFS only
Answer: (A) Subclasses to inherit properties from parent classes
Q#20: Production rules have the form:
(A) IF condition THEN action
(B) BFS node
(C) DFS depth
(D) Random variable
Answer: (A) IF condition THEN action
Q#21: A reasoning system uses knowledge to:
(A) Solve problems and answer queries
(B) Randomly explore nodes
(C) BFS only
(D) DFS only
Answer: (A) Solve problems and answer queries
Q#22: Ontologies in AI define:
(A) Concepts and relationships in a domain
(B) Random BFS nodes
(C) DFS depth only
(D) Heuristic values
Answer: (A) Concepts and relationships in a domain
Q#23: Logic-based reasoning ensures:
(A) Soundness and completeness
(B) Random results
(C) BFS expansion
(D) DFS only
Answer: (A) Soundness and completeness
Q#24: Monotonic reasoning means:
(A) Adding new knowledge does not invalidate old conclusions
(B) Random search
(C) BFS expansion
(D) DFS depth
Answer: (A) Adding new knowledge does not invalidate old conclusions
Q#25: Non-monotonic reasoning allows:
(A) Retracting conclusions based on new evidence
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Retracting conclusions based on new evidence
Q#26: Truth maintenance systems track:
(A) Dependencies among beliefs
(B) BFS nodes
(C) DFS depth
(D) Random values
Answer: (A) Dependencies among beliefs
Q#27: Knowledge representation should be:
(A) Expressive, efficient, and clear
(B) Random symbols
(C) BFS only
(D) DFS only
Answer: (A) Expressive, efficient, and clear
Q#28: Conceptual graphs are:
(A) Graphical representation of knowledge
(B) BFS nodes
(C) DFS depth
(D) Random variables
Answer: (A) Graphical representation of knowledge
Q#29: Frames are similar to:
(A) Objects in object-oriented programming
(B) Random values
(C) BFS nodes
(D) DFS only
Answer: (A) Objects in object-oriented programming
Q#30: Inheritance allows:
(A) Reuse of knowledge
(B) Random assignment
(C) BFS only
(D) DFS only
Answer: (A) Reuse of knowledge
Q#31: Rules and facts are stored in:
(A) Knowledge base
(B) BFS tree
(C) DFS tree
(D) Random database
Answer: (A) Knowledge base
Q#32: Inference engine uses:
(A) Knowledge base to derive new information
(B) Random search
(C) BFS only
(D) DFS only
Answer: (A) Knowledge base to derive new information
Q#33: Deductive reasoning derives:
(A) Specific conclusions from general rules
(B) General rules from data
(C) Random nodes
(D) BFS expansion
Answer: (A) Specific conclusions from general rules
Q#34: Inductive reasoning derives:
(A) General rules from specific observations
(B) Specific conclusions
(C) Random assignments
(D) DFS only
Answer: (A) General rules from specific observations
Q#35: Abductive reasoning finds:
(A) Best explanation for observations
(B) Random moves
(C) BFS nodes
(D) DFS depth
Answer: (A) Best explanation for observations
Q#36: Semantic web uses:
(A) Ontologies for knowledge representation
(B) BFS only
(C) DFS only
(D) Random data
Answer: (A) Ontologies for knowledge representation
Q#37: Closed-world assumption means:
(A) Anything not known to be true is false
(B) All unknowns are true
(C) BFS only
(D) DFS only
Answer: (A) Anything not known to be true is false
Q#38: Open-world assumption means:
(A) Unknown facts may be true or false
(B) All unknowns are false
(C) BFS only
(D) DFS only
Answer: (A) Unknown facts may be true or false
Q#39: Knowledge representation languages include:
(A) Propositional logic, first-order logic, semantic networks, frames
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Propositional logic, first-order logic, semantic networks, frames
Q#40: Semantic networks are suitable for:
(A) Representing hierarchies and relations
(B) Random assignments
(C) BFS only
(D) DFS only
Answer: (A) Representing hierarchies and relations
Q#41: Frames allow:
(A) Default values for attributes
(B) BFS nodes
(C) DFS depth
(D) Random values
Answer: (A) Default values for attributes
Q#42: Inheritance hierarchies avoid:
(A) Repetition of knowledge
(B) Random assignments
(C) BFS expansion
(D) DFS only
Answer: (A) Repetition of knowledge
Q#43: Production systems include:
(A) Rules, working memory, inference engine
(B) Random values
(C) BFS nodes
(D) DFS only
Answer: (A) Rules, working memory, inference engine
Q#44: Working memory stores:
(A) Current facts
(B) Rules only
(C) BFS nodes
(D) DFS only
Answer: (A) Current facts
Q#45: Knowledge representation helps AI to:
(A) Reason, learn, and plan
(B) Random search
(C) BFS only
(D) DFS only
Answer: (A) Reason, learn, and plan
Q#46: In logic-based AI, contradictions can be detected using:
(A) Inference rules
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Inference rules
Q#47: Frames and semantic networks can be combined with:
(A) Rules for reasoning
(B) BFS only
(C) DFS only
(D) Random values
Answer: (A) Rules for reasoning
Q#48: Knowledge representation is crucial for:
(A) Expert systems
(B) Random search
(C) BFS only
(D) DFS only
Answer: (A) Expert systems
Q#49: The choice of representation affects:
(A) Efficiency of reasoning
(B) Randomness
(C) BFS nodes
(D) DFS depth
Answer: (A) Efficiency of reasoning
Q#50: Main goal of knowledge representation in AI is to:
(A) Represent information to enable reasoning and intelligent behavior
(B) Random assignments
(C) BFS only
(D) DFS only
Answer: (A) Represent information to enable reasoning and intelligent behavior