# Artificial Intelligence Questions and Answers – Uncertain Knowledge and Reasoning

This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Uncertain Knowledge and Reasoning”.

1. Using logic to represent and reason we can represent knowledge about the world with facts and rules.
a) True
b) False

Explanation: None.

2. Uncertainty arises in the wumpus world because the agent’s sensors give only ___________
a) Full & Global information
b) Partial & Global Information
c) Partial & local Information
d) Full & local information

Explanation: The Wumpus world is a grid of squares surrounded by walls, where each square can contain agents and objects. The agent (you) always starts in the lower left corner, a square that will be labeled [1, 1]. The agent’s task is to find the gold, return to [1, 1] and climb out of the cave. So uncertainty is there as the agent gives partial and local information only. Global variable are not goal specific problem solving.

3. A Hybrid Bayesian network contains ___________
a) Both discrete and continuous variables
b) Only Discrete variables
c) Only Discontinuous variable
d) Both Discrete and Discontinuous variable

Explanation: To specify a Hybrid network, we have to specify two new kinds of distributions: the conditional distribution for continuous variables given discrete or continuous parents, and the conditional distribution for a discrete variable given continuous parents.

4. How is Fuzzy Logic different from conventional control methods?
a) IF and THEN Approach
b) FOR Approach
c) WHILE Approach
d) DO Approach

Explanation: FL incorporates a simple, rule-based IF X AND Y THEN Z approach to a solving control problem rather than attempting to model a system mathematically.

5. If a hypothesis says it should be positive, but in fact it is negative, we call it ___________
a) A consistent hypothesis
b) A false negative hypothesis
c) A false positive hypothesis
d) A specialized hypothesis

Explanation: Consistent hypothesis go with examples, If the hypothesis says it should be negative but in fact it is positive, it is false negative. If a hypothesis says it should be positive, but in fact it is negative, it is false positive. In a specialized hypothesis we need to have certain restrict or special conditions.

6. The primitives in probabilistic reasoning are random variables.
a) True
b) False

Explanation: The primitives in probabilistic reasoning are random variables. Just like primitives in Propositional Logic are propositions. A random variable is not in fact a variable, but a function from a sample space S to another space, often the real numbers.

7. Which is true for Decision theory?
a) Decision Theory = Probability theory + utility theory
b) Decision Theory = Inference theory + utility theory
c) Decision Theory = Uncertainty + utility theory
d) Decision Theory = Probability theory + preference

Explanation: The Wumpus world is a grid of squares surrounded by walls, where each square can contain agents and objects. The agent (you) always starts in the lower left corner, a square that will be labeled [1, 1]. The agent’s task is to find the gold, return to [1, 1] and climb out of the cave. So uncertainty is there as the agent gives partial and local information only. Global variable are not goal specific problem solving.

8. A constructive approach in which no commitment is made unless it is necessary to do so is ___________
a) Least commitment approach
b) Most commitment approach
c) Nonlinear planning
d) Opportunistic planning

Explanation: Because we are not sure about the outcome.

Sanfoundry Global Education & Learning Series – Artificial Intelligence.