# Artificial Intelligence Questions and Answers Set 2

## Artificial Intelligence

### Questions 11 to 20

 11 What are you predicating by the logic: ۷x: €y: loyalto(x, y). (a)  Everyone is loyal to some one           (b)  Everyone is loyal to all (c)  Everyone is not loyal to someone       (d)  Everyone is loyal (e)  Everyone is not loyal. 12 Which is not Familiar Connectives in First Order Logic? (a)  and                   (b)  iff                      (c)  or                      (d)  not                    (e)  either a or b. 13 Which is not a type of First Order Logic (FOL) Sentence? (a)  Atomic sentences                                                           (b)  Complex sentences (c)  Quantified sentence                          (d)  Quality Sentence (e)  Simple sentence. 14 Which is not a Goal-based agent? (a)  Inference                                          (b)  Search                                             (c)  Planning (d)  Conclusion                                       (e)  Dynamic search. 15 A plan that describe how to take actions in levels of increasing refinement and specificity is (a)  Problem solving                                (b)  Planning (c)  Non-hierarchical plan                         (d)  Hierarchical plan (e)  Inheritance. 16 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 (e)  Problem based planning. 17 Partial order planning involves (a)   Searching over the space of possible plans (b)   Searching over possible situations (c)   Searching the whole problem at once (d)   Searching the best (e)   Searching the goal. 18 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 (e)   Decision Theory = Probability theory + inference. 19 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 (e)  Global information only. 20 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 (e)   Continous variable only.

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1. Anthony, Bob, Christina, and Diane sit around a table that has four seats: North,
East, South and West. We have the following information:
1. Anthony is seated south.
2. Diane sits opposite to Bob.
3. Exactly one of Bob’s neighbors has a glass.
4. A glass stands on the table positioned north.
5. If Diane has a glass then her two neighbors have a glass as well.
6. The neighbor to Anthony’s right (from his point of view) has a glass.
You have the task to model the given situation with the help of formulas of
propositional logic. Use the following variables:
{xy|x 2 {A,B,C,D}, y 2 {N,O, S,W}} = {AN,AO,AS,AW,BN, ...,DS,DW}
For example, the variable AN is true, if and only if Anthony is seated North
of the table. Furthermore, the variables {A,B,C,D,N,O, S,W} can be used to
describe the position of the glasses: The variables A ... D are true, if and only if
there is a glass in front of person A ... D, respectively. The variables N ... W are
true, if and only if there is a glass at the respective position on the table.
Write formulas of propositional logic to model the information (1) to (6) given
above. (Remember that you can use implications!)
Resolution
Knowledge: W = (X _ F _ ¬M _ R) ^ (¬F _ X _ B) ^ (¬R _ ¬F _ X _ ¬B) ^
(X _ F _M) ^ (X _ ¬M _ ¬R _ F) ^ (¬F _ X _ R _ ¬A _ ¬B) ^ ¬X
Hypothesis: H = ¬(¬F _ X _ ¬B _ R _ A)
Question: Does W |= H hold?
Apply the resolution method! (Note that the hypothesis is already nearly in
CNF; just remove the first negation and start the resolution.)

1. you still need an answer for this?

2. plz solve me these two questions iam confuse plz help me post the solution of these two tasks in artificial intelligence

Anthony, Bob, Christina, and Diane sit around a table that has four seats: North,
East, South and West. We have the following information:
1. Anthony is seated south.
2. Diane sits opposite to Bob.
3. Exactly one of Bob’s neighbors has a glass.
4. A glass stands on the table positioned north.
5. If Diane has a glass then her two neighbors have a glass as well.
6. The neighbor to Anthony’s right (from his point of view) has a glass.
You have the task to model the given situation with the help of formulas of
propositional logic. Use the following variables:
{xy|x 2 {A,B,C,D}, y 2 {N,O, S,W}} = {AN,AO,AS,AW,BN, ...,DS,DW}
For example, the variable AN is true, if and only if Anthony is seated North
of the table. Furthermore, the variables {A,B,C,D,N,O, S,W} can be used to
describe the position of the glasses: The variables A ... D are true, if and only if
there is a glass in front of person A ... D, respectively. The variables N ... W are
true, if and only if there is a glass at the respective position on the table.
Write formulas of propositional logic to model the information (1) to (6) given
above. (Remember that you can use implications!)
Resolution
Knowledge: W = (X _ F _ ¬M _ R) ^ (¬F _ X _ B) ^ (¬R _ ¬F _ X _ ¬B) ^
(X _ F _M) ^ (X _ ¬M _ ¬R _ F) ^ (¬F _ X _ R _ ¬A _ ¬B) ^ ¬X
Hypothesis: H = ¬(¬F _ X _ ¬B _ R _ A)
Question: Does W |= H hold?
Apply the resolution method! (Note that the hypothesis is already nearly in
CNF; just remove the first negation and start the resolution.)