Knowledge representation: logic, semantic networks, frames, rules, expert systems and uncertainty handling. - One Line Questions

1. The statement 'All men are mortal' can be represented in predicate logic as: — ∀x (Man(x) → Mortal(x))
2. What is the logical operator that represents disjunction (OR)? — ∨
3. What is the logical connective for 'NOT'? — ¬
4. In logic, what is a 'Horn clause'? — A clause with at most one positive literal
5. In logic, what is an 'atom' or 'atomic sentence'? — A simple declarative sentence that cannot be broken down further
6. In a semantic network, what does an 'IS-A' link typically represent? — A subclass relationship
7. In predicate logic, what is a 'term'? — A variable, constant, or function applied to terms
8. What is a 'tautology' in propositional logic? — A statement that is always true
9. In predicate logic, what is a proposition that contains variables and quantifiers called? — Predicate
10. What is the main advantage of using frames over simple semantic networks? — More structured way to represent stereotypical knowledge and inheritance
11. In propositional logic, what is the connective that represents 'if and only if'? — Biconditional (IF AND ONLY IF)
12. In predicate logic, a statement like 'P(x)' where 'x' is a variable is called a: — Predicate
13. What is the primary challenge in building a comprehensive knowledge base for an expert system? — The difficulty and time-consuming nature of knowledge acquisition and representation
14. What is the main limitation of using simple 'IF-THEN' rules for knowledge representation in complex domains? — Can become difficult to manage and maintain as the number of rules grows
15. What is the primary disadvantage of using semantic networks for complex knowledge representation? — Lack of formal semantics and ambiguity
16. What is the main characteristic of a 'fuzzy set'? — Elements have a degree of membership between 0 and 1
17. In predicate logic, what is the existential quantifier '∃' used to denote? — There exists
18. A production rule typically consists of two parts: IF (condition) THEN (action). What is this structure called? — Rule
19. Which type of knowledge representation uses nodes to represent concepts and arcs to represent relationships between concepts? — Semantic Networks
20. Which method of handling uncertainty assigns a degree of belief to a proposition, typically between 0 and 1? — Probability Theory
21. Which method for handling uncertainty uses a directed acyclic graph to represent probabilistic relationships between variables? — Bayesian Networks
22. What does the 'modus ponens' inference rule state? — If P implies Q, and P is true, then Q is true.
23. Which type of slot in a frame is used to specify a default value for an attribute? — Default
24. Which of the following is NOT a standard type of slot in a frame? — If-then
25. Which component of an expert system is responsible for acquiring knowledge from human experts? — Knowledge Acquisition Module
26. What is the term for a set of facts and rules used by an expert system to solve problems? — Knowledge Base
27. Which type of relationship in a semantic network signifies that one concept is an instance of another concept? — IS-INSTANCE-OF
28. What does 'resolution' as an inference rule achieve in predicate logic? — It is a refutation complete inference rule that can derive new clauses from existing ones
29. Which rule of inference is used to infer a conclusion from a conditional statement and the negation of its consequent? — Modus Tollens
30. Which AI system is designed to emulate the decision-making ability of a human expert in a specific domain? — Expert System
31. In first-order logic, what is the term for a sentence that contains no variables? — Ground term
32. Which theory of uncertainty combines evidence from different sources and can handle ignorance (lack of evidence)? — Dempster-Shafer Theory
33. Which approach to uncertainty models degrees of truth rather than degrees of belief? — Fuzzy Logic
34. Which knowledge representation technique is best suited for representing declarative knowledge? — Logic
35. Which of the following is a method for representing and reasoning with imprecise or vague information? — Fuzzy Logic
36. What is a 'default reasoning' mechanism in AI? — Reasoning that assumes certain facts are true unless proven otherwise
37. What is the main challenge in handling uncertainty in AI systems? — Dealing with incomplete or imprecise information
38. What does the 'inheritance' mechanism in frames allow? — Properties to be passed down from more general frames to more specific ones
39. What is the 'frame problem' in AI? — The problem of efficiently representing and updating the vast amount of information that remains unchanged when an action occurs
40. What is a 'knowledge acquisition bottleneck' in the context of expert systems? — The slow and difficult process of extracting knowledge from experts
41. In a frame system, what is a 'slot filler'? — The value associated with a slot
42. In knowledge representation, what is 'ontological commitment'? — The set of entities and relationships that a knowledge representation system assumes to exist
43. What does the universal quantifier '∀' represent in predicate logic? — For all
44. What is the main advantage of using semantic networks for representing common-sense knowledge? — They are intuitive and can represent relationships like inheritance and association effectively
45. What is the primary goal of a 'truth maintenance system' in AI? — To manage and update beliefs when new information is added or contradictions arise
46. What is the primary purpose of a frame in knowledge representation? — To represent stereotypical situations or objects with slots for attributes
47. What is the role of the 'inference engine' in an expert system? — To apply rules to the data to derive conclusions
48. What is the purpose of the 'explanation facility' in an expert system? — To allow the system to explain its reasoning process to the user
49. In an expert system, what is the 'working memory' used for? — To store the current state of the problem and facts derived during reasoning
50. What is the primary function of the 'forward chaining' inference strategy? — To start with known facts and apply rules to derive new facts until a goal is reached
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