HamiIT
Sign inGet started
Home
ADD CONTENT

Sign in Required

Please sign in to add content

Sign In
ProgramsBsc CSITSemester 4Artificial Intelligence Unit III: Problem Solving by Searching (9 Hrs.)
Chapter Study

Bsc CSIT Semester 4 – Artificial Intelligence – Unit III: Problem Solving by Searching (9 Hrs.)

Comprehensive questions and detailed answers for Unit III: Problem Solving by Searching (9 Hrs.). Perfect for exam preparation and concept clarity.

18
Questions
130
Marks
Back to All Chapters
1

How is informed search different from uninformed search? Create a state space with appropriate heuristics, now illustrate how hill climbing search expands nodes to reach a goal. Modify the state space heuristics and demonstrate when the hill climbing will not be complete.

HardTHEORY10 marks2081(TU Final)
2

How uniform cost search is used to search goal in the state apace ? Illustrate with example.

MediumTHEORY5 marks2081(TU Final)
3

How is minmax algorithm used in game search? Consider state space is defined by a collection of pairs like (A, B) representing paths between states A and B. Construct state space for following and use a minmax algorithm

(A, B), (A, C), (B, D), (D, E), (C, F), (C, G), (D, H), (D, I), (E, J), (F, K), (F, L), (G, M), (G, N).

The utilities for states H, I, J, K, L, M, N are 1, 3, 2, 6, 3, 4, 1 respectively.

MediumTHEORY5 marks2081(TU Final)
4

Define state space graph. Differenciate between A* search and greedy best first search.

HardTHEORY10 marks2080(TU Final)
5

What is game search? How minmax search used in game playing ? Illustrate with an example.

MediumTHEORY5 marks2080(TU Final)
6

What is constraint satisfaction problem? Illustrate graph coloring problem as constraint satisfaction problem.

MediumTHEORY5 marks2080(TU Final)
7

Define admissible heuristic with an example. Explain the working mechanism and limitations of hill climbing search.

HardTHEORY10 marks2079(TU Final)
8

How do you define problem? What are criteria for defining problem? Compare Constraint Satisfaction Problem and Real World Problem in detail with appropriate example.

HardTHEORY10 marks2079(TU Final)
9

What is state space representation? Illustrate with one example.

HardTHEORY5 marks2079(TU Final)
10

Define game. Write the benefits and limitations of depth limited search.

HardTHEORY5 marks2079(TU Final)
11

How informed search are different than uniformed? Given following stae space, illustrate how depth limited search and iterative depending dearch works? Use your own assumption for depth search.

image

Hence, A is start and K is goal.

HardTHEORY10 marks2078(TU Final)
12

Consider following facts

Every traffic chases driver. Every driver who horns is smart. No traffic catches any smart driver. Any traffic who chases some driver but does not catch him frusted. Now configure FoPL knowledge base for above statements. Use resolution algorithm to draw a conclusion that “If all drivers horn, then all traffics are frusted.”

HardTHEORY10 marks2078(TU Final)
13

Given following search space, determine if these exists any alpha and beta cutoffs.

image

MediumTHEORY5 marks2078(TU Final)
14

Construct a state space with appropriate heuristics and local costs. Show that Greedy Best First search is not complete for the state space. Also illustrate A* is complete and guarantees solution for the same state space.

HardTHEORY10 marks2076(TU Final)
15

Illustrate with an example, how uniform cost search algorithm can be used for finding goal in a state space.

MediumTHEORY5 marks2076(TU Final)
16

Define state space graph. Differentiate between A* search and greedy best first search.

HardTHEORY10 marks2080(TU Final)
17

What is game search? How Min–Max search is used in game playing? Illustrate with an example.

MediumTHEORY5 marks2080(TU Final)
18

What is constraint satisfaction problem? Illustrate graph coloring problem as constraint satisfaction problem.

MediumTHEORY5 marks2080(TU Final)
Showing 18 questions

Questions in Unit III: Problem Solving by Searching (9 Hrs.)

How is informed search different from uninformed search? Create a state space with appropriate heuristics, now illustrate how hill climbing search expands nodes to reach a goal. Modify the state space

Marks: 10

Year: 2081 Final TU

How is informed search different from uninformed search? Definitions - Uninformed search (also called blind search) is when the algorithm has no additional information beyond the problem definiti

How uniform cost search is used to search goal in the state apace ? Illustrate with example.

Marks: 5

Year: 2081 Final TU

How is Uniform Cost Search used to find a goal in the state space? Definition Uniform Cost Search is an uninformed search algorithm that expands nodes in order of increasing cumulative cost from

How is minmax algorithm used in game search? Consider state space is defined by a collection of pairs like (A, B) representing paths between states A and B. Construct state space for following and use

Marks: 5

Year: 2081 Final TU

How is the minimax algorithm used in game search? The minimax algorithm is a recursive adversarial search technique used in two‑player, zero‑sum games where one player tries to maximize a value and

Define state space graph. Differenciate between A search and greedy best first search.

Marks: 10

Year: 2080 Final TU

Definition: State Space Graph A state-space graph is a representation of all possible configurations (states) of a problem along with the transitions (actions) that take you from one state to anothe

What is game search? How minmax search used in game playing ? Illustrate with an example.

Marks: 5

Year: 2080 Final TU

What is Game Search? Game search is a technique in AI used to find the best possible move in a competitive game where players take turns. - Examples: Chess, Tic-Tac-Toe, Checkers. - AI evaluates p

What is constraint satisfaction problem? Illustrate graph coloring problem as constraint satisfaction problem.

Marks: 5

Year: 2080 Final TU

What is a Constraint Satisfaction Problem (CSP)? A Constraint Satisfaction Problem (CSP) is a problem where: - We need to assign values to variables. - Each variable has a domain of possible values. -

Define admissible heuristic with an example. Explain the working mechanism and limitations of hill climbing search.

Marks: 10

Year: 2079 Final TU

Admissible Heuristic An admissible heuristic is a heuristic function that never overestimates the actual cost of reaching the goal. It always gives a value ≤ true cost, which guarantees optimality i

How do you define problem? What are criteria for defining problem? Compare Constraint Satisfaction Problem and Real World Problem in detail with appropriate example.

Marks: 10

Year: 2079 Final TU

What is a Problem in AI? A problem in AI is a situation where an agent must move from an initial state to a goal state using a sequence of actions. It is defined clearly so that a search algorithm can

What is state space representation? Illustrate with one example.

Marks: 5

Year: 2079 Final TU

State Space Representation State space representation is a method to describe a problem using states and transitions between them. - State: A configuration of the problem - Initial State: Where th

Define game. Write the benefits and limitations of depth limited search.

Marks: 5

Year: 2079 Final TU

Definition of a Game In AI, a game is a scenario where: - Two or more players take turns, - The outcome depends on moves of all players, - Goal is to maximize own benefit while minimizing opponent’s.

How informed search are different than uniformed? Given following stae space, illustrate how depth limited search and iterative depending dearch works? Use your own assumption for depth search. Hence,

Marks: 10

Year: 2078 Final TU

Answer (a) Difference between Informed and Uninformed Search (3 Marks) | Feature | Uninformed Search (Blind Search) | Informed Search (Heuristic Search) | |---------|---------------------------------

Consider following facts Every traffic chases driver. Every driver who horns is smart. No traffic catches any smart driver. Any traffic who chases some driver but does not catch him frusted. Now confi

Marks: 10

Year: 2078 Final TU

First-Order Predicate Logic Knowledge Base and Resolution Proof Step 1: Define Predicates and Knowledge Base Predicates: - T(x): x is a traffic - D(x): x is a driver - H(x): x horns - S(x): x is s

Given following search space, determine if these exists any alpha and beta cutoffs.

Marks: 5

Year: 2078 Final TU

Alpha-Beta Cutoff Analysis The given tree is a Minimax tree with MAX at the root (A). We need to check if any alpha (α) or beta (β) cutoffs exist. Step 1: Leaf node values - H = 2, I = 4 - J = 6, K

Construct a state space with appropriate heuristics and local costs. Show that Greedy Best First search is not complete for the state space. Also illustrate A is complete and guarantees solution for t

Marks: 10

Year: 2076 Final TU

Constructing State Space and Heuristic Analysis 1. State Space Construction Consider a simple graph from Start (S) to Goal (G): - Nodes: S, A, B, C, G - Local Costs (edge costs g(n)): - S -> A =

Illustrate with an example, how uniform cost search algorithm can be used for finding goal in a state space.

Marks: 5

Year: 2076 Final TU

Uniform Cost Search (UCS) Algorithm Uniform Cost Search is a search algorithm used to find the least-cost path from a start node to a goal node in a state space. - It expands the node with the lowes

Define state space graph. Differentiate between A search and greedy best first search.

Marks: 10

Year: 2080 Final TU

State Space Graph and Search Strategies 1. Definition: State Space Graph A state space graph is a graphical representation of all possible states of a problem along with the transitions (actions) bet

What is game search? How Min–Max search is used in game playing? Illustrate with an example.

Marks: 5

Year: 2080 Final TU

Game Search and Min–Max Algorithm in Game Playing 1. What is Game Search? - Definition: Game search is a technique in AI used to determine optimal moves in games where two or more players compete.

What is constraint satisfaction problem? Illustrate graph coloring problem as constraint satisfaction problem.

Marks: 5

Year: 2080 Final TU

Constraint Satisfaction Problem (CSP) and Graph Coloring Example 1. What is a Constraint Satisfaction Problem (CSP)? - Definition: A CSP is a problem defined by: 1. A set of variables \(X = \{X1, X

About Unit III: Problem Solving by Searching (9 Hrs.) Questions

This page contains comprehensive questions from the Unit III: Problem Solving by Searching (9 Hrs.) chapter of Artificial Intelligence , part of the Bsc CSIT Semester 4 curriculum. All questions include detailed model answers from past TU exam papers.

Study Tips

  • Review concepts before attempting questions
  • Practice writing complete answers
  • Compare your answers with model solutions
  • Focus on questions from recent years
  • Use direct links (#question-ID) to bookmark and share specific questions

Related Resources

← Back to Artificial Intelligence Chapters

Unit III: Problem Solving by Searching (9 Hrs.) chapter questions with answers for Artificial Intelligence (Bsc CSIT Semester 4). Prepare for TU exams with our comprehensive question bank and model answers.

H
Hami IT

Empowering IT students with quality education resources and comprehensive exam preparation materials.

Programs

  • Flutter
  • Java
  • DevOps

Company

  • About Us
  • Contact

Contact

  • 📧hamiit.dev@gmail.com
  • 📞+977 9813706443
  • 📍Kathmandu, Nepal

© 2026 Hami IT. All rights reserved.