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Artificial Intelligence BS 3 Semester/Term UOS — University of Sargodha 2025

Artificial Intelligence BS/MS Software Engineering/PhD Software Engineering 3 Semester/Term UOS — University of Sargodha 2025 — page 1

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  • Ayesha Mustafa· 23 hours ago

    BS ZOOLOGY first semester Animal diversity ZOOL 101 - university of Punjab 2025

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  • Abubakar· 1 day ago

    Literary criticism

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  • Guest· 1 day ago

    this paper consists of 60 marks but now we have 35 marks paper.

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  • Annie· 2 days ago

    Can you please tell me more past papers please because my exams are starting from next week

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    Did you provide the past papers of the science of society uos?

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Paper text

Course Code: CMPC-5207

Date: 04-11-2025

University of Sargodha

Department of Software Engineering

Artificial Intelligence (AT)

Time: 60 minutes

Class: BS Software Engineering 3rd Regular

Attempt Any 5 Questions

Marks: 20

(Mid-Term)

(Bloom: C2-Understand | CLO_2|PLO_2)

(*5= 10 Marks)

Q1: What is the Turing Test? Mention any two capabilities required fer a machine to pas it?

Q2: Why is exhaustive search not a practical solution for the Traveling Salesperson Praokee when he amber of

cities becomes large? (Bloom: C2-Understand | CLO |PLO_2)

PLO.2)

03: What is an admissible heuristic? Explain its imporance in A Ser:h? (Boom: C-Uaderand /CLO?

Q4: Define Swarm Intelligence and give ane example from anare? (Blom: C-Undertand| CLOZIRLO.3)

Q5: How does Simulated Annealing overcome the problem of bocal matims? Ey in the tol of epera?

(Bloom: C2-Understand | CLO_2| PLO_2)

Q6: What is an Expent Systern? Briefly explain the role of is inferente engine? (Blase: C2-Cadertned) CLO.2

(PLO_2)

(52:10.Mart)

Attempt Any 2 Questions

07. Uninformed and Informed Search

a) Explain Uniform Cost Search (UCS) and state how it differs from Breath First Search (BFS).

(2 marks)

(Bloom: C2-Understand | CLO 2| PLO

2)

b) Consider a search problem where the path cost Vg(n)-61) and the hersic esimate (5(0)~df) Cakult the

evaluation value (fa)) using A* Seach (3 mark) (Bloom: C3-Appls (CLO 3/PLO

4)

o) Explain why A• Search can find an optimal solution when an admisis bursts is used (2 marks) Bloca

C2-Understand| CLO_2/PLO_2)

Q8. Case Study: Optimization Using Local Search

delivery company has to visit several cities and retura to is staring civ le goulis to find a tour with the

w total distance. The company initrally gelerates a possible tour, had the lie is bot epinal A seple hill

leorithm improves the tour unt it cannot find a better neighboring alden. However, the alerte ray

ntimum even when a better tour exists elsewbere.

questions:

described in this case stuty and stare its main oystive (1 mars) (Bloen: CI

the initial tour and why it may fail to find the global optimum (2 reaks)

- compasy escape a local optimam (2 minks) (Ble:

C).-