AI Sentences


Q.                             Consider the following sentences:

·         John likes at least one dish Jane likes.
·         Everybody likes some food
·         Whenever someone likes at least one spicy dish, they’re happy.
·         Every city has a dogcatcher who has been bitten by every dog in town.

Translate these sentences into formulas in predicate logic.

Ans.:
·         John likes at least one dish Jane likes.
                         $F food (F) Ù  likes (Jane, F) Ù likes (john, F)

·         Everybody likes some food
"X $F food (F) Ù  likes (X, F)
·         Whenever someone likes at least one spicy dish, they’re happy.
          "X $F food (F) Ù spicy (F) Ù eats (X, F) ®     happy(X)

·         Every city has a dogcatcher who has been bitten by every dog in town.
"T $C "D city(C) ® (dogcatcher(C, T) Ù   (dog (D) Ù lives-in (D, T) ® bit (D, C)) )

AI inheritable knowledge


Q.                       Generate an example that shows how inheritable knowledge works.
Answer:    Example that shows how inheritable knowledge works:

Consider the word “college”. A “college” has certain features like it will have classrooms, teacher, a playground, building, students, office etc. Further, the classrooms will have a blackboard, cupboard, furniture, students etc. Besides these, there will be some general concepts regarding the functioning of the college, like it will have time table for each class, fee deposit plan, examination pattern, course module, cultural activity etc.

AI


1.     Show how mean-ends analysis could be used to solve a problem of getting one place to another. Assume that the available operators are like walk, drive, take the bus, take a cab, and fly?

Answer: Means and Ends Analysis: This method of search attempts to reduce the gap between the current state and the goal state. One simple way to explore this method is to measure the distance between the current state and the goal, and then apply an operator to the current state, so that the distance between the resulting state and the goal is reduced.
 Algorithm: The means ends analysis (Current state, goal state)
Step # 1: compare the current state with that of goal state and if there are differences between them then return,
Else,
Step # 2: select the important difference and try to reduce it by doing the following until a success or failure is being found:
(i) Select an un-tired operator O that is applicable to the current difference, if there are no operators then signal is failure
(ii) And select an operator O that is applicable to the current difference, if there is no operator O to the current state. Compute and/or generate two of the descriptions. O-START state, a state in which O’s preconditions are satisfied and O-RESULT that results when O is applied to O-START state.
(iii) If (FIRST- ONE <- Means-ends analysis (current, O- the start) and (the Last <- One Means – ends – analysis (O – the Result and, Goal state) are successful, then the return success by concatenating the First -One and the Last -One state.
Drive
Walk
Fly
Cab
Yes
Yes

Bus
Yes


Get cab empty
Yes
Yes

Get bus empty
Yes
Yes

Putting object
Yes
Yes


Using these prediction we can choose easy way to solve the Problem.