ASSIGNMENTOf

ARTIFICIAL INTELLIGENCE

SUBMITTED BY:- SUBMITTED TO:- RICHA Mr. Anup NandyB.Tech CSESection-RB1802 Roll no-A11Reg.No=10801657

Part-AQ=1:- Check whether the following argument is valid:If Paul lives in Dublin, he lives in Ireland. Paul lives in Ireland. Therefore Paul lives in Dublin.

(i) Represent the argument formally; (ii) Use truth tables to prove or disprove the validity of the

argument.

(iii) Build a counterexample is not valid.Ans:- If Paul lives in Dublin, he lives in Ireland. Paul lives in Ireland. Therefore Paul lives in Dublin.(i) Give the keys of your formalization using PL; (ii) represent the argument for- mally; and (iii) Apply the truth table method to prove or disprove the validity of the argument. (iv) Build a counterexample if the argumentation is not valid.

KB |= α

{p → i, i} |= d

KB ∪ {¬α}

{p → i, i, ¬d}

Q=2:- Three boxes are presented to you. One contains gold, the other two are empty. Each box has imprinted on it a clue as to its contents; the clues are (Box 1) “The gold is not here”, (Box 2) “The gold is not here”, and (Box 3) “the gold is in Box 2”. Only one message is true; the other two are false. Which box has the gold? Formalize the puzzle in PL and find the solution using a truth table if the argumentation?Ans:- The gold is in the Box 1.

Q=3:- Compare Declarative and Procedural knowledge and describe the areas in which each can be applied.Ans:- Ontology’s on the Semantic Web are by nature decentralized. From the body of ontology mapping approaches, we can draw a conclusion that an effective approach to automate ontology mapping requires both data and metadata in application domains. Most existing approaches usually represent data and metadata by ad-hoc data structures, which lack formalisms to capture the underlying semantics. Furthermore, to approach semantic interoperability, there is a need to represent mappings between ontology’s with well-defined semantics that guarantee accurate exchange of information. To address these problems, we propose that domain ontology’s attached with extraction procedures are capable of representing knowledge required to find direct and indirect matches between ontology’s. And mapping ontology’s attached with query procedures not only support equivalent inferences and computations on equivalent concepts and relations but also improve query performance by applying query procedures to derive target-specific views. We conclude that a combination of declarative and procedural representation based on ontology’s favors the analysis and implementation for ontology mapping that promises accurate and efficient semantic interoperability.

Part-BQ=4:- Determine whether each of the following sentence is Satisfiable, Contradictory or Valid

a. P V Q & ~P V ~ Q & P & Q

Ans:-

P Q ~P ~Q PvQ ~Pv~Q

0 0 1 1 0 1

1 0 0 1 0 0

0 1 1 0 0 0

1 1 0 0 1 0

b. P → ~Q → ~P

Ans:-

P Q ~P ~Q P=>~Q P=>~Q=>~P

0 0 1 1 1 1

1 0 0 1 1 1

0 1 1 0 1 1

1 1 0 0 1 1

c. (P V Q) & (~P V Q) & P

Ans:-

P Q ~P PvQ ~PvQ

0 0 1 0 0

1 0 0 0 0

0 1 1 0 1

1 1 0 1 0

d. (P & Q) → R V ~ Q

Ans:-

P Q ~Q Q=>R Q=>Rv~Q

0 0 1 1 1

1 0 1 1 1

0 1 0 1 0

1 1 0 1 0

e. (P & Q) → ~(P V Q)

Ans:-

P Q ~P Q=>~P Q=>~PvQ

0 0 1 1 0

1 0 0 1 0

0 1 1 1 1

1 1 0 1 1

Q=5:- Given the following PL expressions, place parenthesis in the

appropriate places to form fully abbreviated wffs.

a. ~P V Q & R S U & Q

b. P &~Q V P U ~ R

c. Q V P V ~R & S ~U & P R

Ans:- “a” part is the correct answer of this question. That can be describe

in the following tables. Table 1:-

P Q ~P ~PvQ

0 0 1 0

1 0 0 0

0 1 1 1

1 1 0 0

Table 2:-

R S U R->S R->S->U

0 0 0 1 0

0 0 1 1 1

0 1 0 1 0

0 1 1 1 1

1 0 0 0 1

1 0 1 0 1

1 1 0 1 0

1 1 1 1 1

Q=6:- Consider the following sentences:

“Mary likes all kinds of food. Pizza is a kind of food. Apple is a food.

Anything anyone eats is a food. John eats chicken. Ana eats everything

Mary eats.”

Translate these sentences into Predicate Logic. Convert the formulae into

clauses. Use resolution algorithm to answer the following question:

“What food does Ana eat?”

Prove that “Mary likes chicken”

Ans:- 1) V(x)food(x)=>mary(x)

2) V(y,x)food(x)=>pizza(x).

3) food(apple).

4) V(x) food (x) AND(operator)any_one(x)

5) chicken(John).

6) Ana(x) AND (operator) Mary(x)=>eats(y).