MCQOPTIONS
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MCQOPTIONS
This section includes 41 Mcqs, each offering curated multiple-choice questions to sharpen your Artificial Intelligence knowledge and support exam preparation. Choose a topic below to get started.
| 1. |
What is probability density function? |
| A. | Probability distributions |
| B. | Continuous variable |
| C. | Discrete variable |
| D. | Probability distributions for Continuous variables |
| Answer» E. | |
| 2. |
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 |
| Answer» B. Most commitment approach | |
| 3. |
What is true about semantic net? |
| A. | A way of representing knowledge |
| B. | Semantic network are Data Structure |
| C. | Semantic network are Data Type |
| D. | None of the above |
| Answer» B. Semantic network are Data Structure | |
| 4. |
_______ defines the relationship between a term denoting the whole and a term denoting a part of, or a member of, the whole. |
| A. | Holinymy |
| B. | Holonymy |
| C. | Holonimy |
| D. | Holonimi |
| Answer» C. Holonimy | |
| 5. |
Which of the following is/are correct advantage of Semantic nets? |
| A. | Easy to understand |
| B. | Efficient in space requirement |
| C. | Easy to visualise |
| D. | All of the above |
| Answer» E. | |
| 6. |
A denotes opposite of B is? |
| A. | Synonymy relation |
| B. | Antonymy relation |
| C. | both a and b |
| D. | None of the above |
| Answer» C. both a and b | |
| 7. |
In semantic nets, to find relationships among objects are determined by spreading activation out from each of 2 nodes and identify where the activation meets. This process is called? |
| A. | Associative Search |
| B. | Object Search |
| C. | Knowledge Search |
| D. | Intersection Search |
| Answer» E. | |
| 8. |
Which of the following are the Semantic Relations used in Semantic Networks? |
| A. | Meronymy |
| B. | Holonymy |
| C. | Hyponymy |
| D. | All of the above |
| Answer» E. | |
| 9. |
Semantic nets originally proposed by? |
| A. | Andrew Ng |
| B. | M. Ross Quillian |
| C. | Demis Hassabis |
| D. | Yoshua Bengio |
| Answer» C. Demis Hassabis | |
| 10. |
As nodes are associated with other nodes semantic nets are also referred as? |
| A. | Associative nets |
| B. | Structure nets |
| C. | Knowledge nets |
| D. | Arcs nets |
| Answer» B. Structure nets | |
| 11. |
Semantic nets originally proposed in? |
| A. | 1950 |
| B. | 1960 |
| C. | 1970 |
| D. | 1980 |
| Answer» C. 1970 | |
| 12. |
The central idea of partitioning is to allow groups, nodes and arcs to be bundled together into units called? |
| A. | quantification |
| B. | spaces |
| C. | networks |
| D. | hendrix |
| Answer» C. networks | |
| 13. |
Semantic nets consists of? |
| A. | Node |
| B. | Edges |
| C. | Labels |
| D. | All of the above |
| Answer» E. | |
| 14. |
Links or arcs apperar as arrow to express the relationship between? |
| A. | Nodes |
| B. | Edges |
| C. | Objects |
| D. | Labels |
| Answer» D. Labels | |
| 15. |
Which of the following is an extension of the semantic network? |
| A. | Expert Systems |
| B. | Rule Based Expert Systems |
| C. | Decision Tree Based networks |
| D. | Partitioned Networks |
| Answer» E. | |
| 16. |
A denotes same as B is? |
| A. | Synonymy relation |
| B. | Antonymy relation |
| C. | both a and b |
| D. | None of the above |
| Answer» B. Antonymy relation | |
| 17. |
Which graph is used to represent semantic network? |
| A. | Undirected graph |
| B. | Directed graph |
| C. | Directed Acyclic graph |
| D. | Directed complete graph |
| Answer» C. Directed Acyclic graph | |
| 18. |
A hyponym shares a type-of relationship with its _________. |
| A. | Node |
| B. | Edges |
| C. | Hypernym |
| D. | Labels |
| Answer» D. Labels | |
| 19. |
Which of the following are correct disadvantage of Semantic nets? |
| A. | Attributes not described |
| B. | No standard about nodes |
| C. | Inheritance can cause problems |
| D. | All of the above |
| Answer» E. | |
| 20. |
Hendrix partitioned a semantic network whereby a semantic network, loosely speaking, can be divided into? |
| A. | one or more networks |
| B. | two or more networks |
| C. | three or more networks |
| D. | four or more networks |
| Answer» B. two or more networks | |
| 21. |
Bayesian Belief Network is also known as ? |
| A. | belief network |
| B. | decision network |
| C. | Bayesian model |
| D. | All of the above |
| Answer» E. | |
| 22. |
The generalized form of Bayesian network that represents and solve decision problems under uncertain knowledge is known as an? |
| A. | Directed Acyclic Graph |
| B. | Table of conditional probabilities |
| C. | Influence diagram |
| D. | None of the above |
| Answer» D. None of the above | |
| 23. |
How many component does Bayesian network have? |
| A. | 2 |
| B. | 3 |
| C. | 4 |
| D. | 5 |
| Answer» B. 3 | |
| 24. |
Bayesian Network consist of ? |
| A. | 2 components |
| B. | 3 components |
| C. | 4 components |
| D. | 5 components |
| Answer» B. 3 components | |
| 25. |
The nodes and links form the structure of the Bayesian network, and we call this the ? |
| A. | structural specification |
| B. | multi-variable nodes |
| C. | Conditional Linear Gaussian distributions |
| D. | None of the above |
| Answer» B. multi-variable nodes | |
| 26. |
If we have variables x1, x2, x3,....., xn, then the probabilities of a different combination of x1, x2, x3.. xn, are known as? |
| A. | Table of conditional probabilities |
| B. | Causal Component |
| C. | Actual numbers |
| D. | Joint probability distribution |
| Answer» E. | |
| 27. |
Which of the following are used for modeling times series and sequences? |
| A. | Decision graphs |
| B. | Dynamic Bayesian networks |
| C. | Value of information |
| D. | Parameter tuning |
| Answer» C. Value of information | |
| 28. |
Bayesian networks are a factorized representation of the full joint. |
| A. | True |
| B. | False |
| C. | Can be true or false |
| D. | Can't Say |
| Answer» B. False | |
| 29. |
The Distributive law simply means that if we want to marginalize out the variable A we can perform the calculations on the subset of distributions that contain A. |
| A. | True |
| B. | False |
| C. | Can be true or false |
| D. | Can't Say |
| Answer» B. False | |
| 30. |
The Bayesian network graph does not contain any cyclic graph. Hence, it is known as a |
| A. | DCG |
| B. | DAG |
| C. | CAG |
| D. | SAG |
| Answer» C. CAG | |
| 31. |
In a Bayesian network variable is? |
| A. | continuous |
| B. | discrete |
| C. | both a and b |
| D. | None of the above |
| Answer» D. None of the above | |
| 32. |
____________ is the process of calculating a probability distribution of interest e.g. P(A | B=True), or P(A,B|C, D=True). |
| A. | Diagnostics |
| B. | Supervised anomaly detection |
| C. | Inference |
| D. | Prediction |
| Answer» D. Prediction | |
| 33. |
When we query a node in a Bayesian network, the result is often referred to as the marginal. |
| A. | True |
| B. | False |
| C. | Can be true or false |
| D. | Can't Say |
| Answer» B. False | |
| 34. |
Where does the dependence of experience is reflected in prior probability sentences? |
| A. | Syntactic distinction |
| B. | Semantic distinction |
| C. | Both a & b |
| D. | None of the mentioned |
| Answer» B. Semantic distinction | |
| 35. |
A constructive approach in which no commitment is made unless it is necessary to do so, i? |
| A. | Least commitment approach |
| B. | Most commitment approach |
| C. | Nonlinear planning |
| D. | Opportunistic planning |
| Answer» B. Most commitment approach | |
| 36. |
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 |
| Answer» D. Decision Theory = Probability theory + preference | |
| 37. |
The primitives in probabilistic reasoning are random variables. |
| A. | True |
| B. | False |
| Answer» B. False | |
| 38. |
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 |
| Answer» D. A specialized hypothesis | |
| 39. |
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 |
| Answer» B. Only Discrete variables | |
| 40. |
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 |
| Answer» D. Full & local information | |
| 41. |
Using logic to represent and reason we can represent knowledge about the world with facts and rules. |
| A. | True |
| B. | False |
| Answer» B. False | |