(SEM VII) THEORY EXAMINATION 2022-23 ARTIFICIAL INTELLIGENCE

B.Tech Arts 0 downloads

₹29.00

ARTIFICIAL INTELLIGENCE (KCS071)

B.Tech SEM VII – Complete Solved Question Paper (2022–23)

SECTION A

Attempt all questions in brief (2 × 10 = 20 Marks)

(a) Define Artificial Intelligence. Is it different from intelligence?

Artificial Intelligence (AI) is a branch of computer science that aims to create machines capable of performing tasks that normally require human intelligence such as learning, reasoning, and decision-making.

Yes, AI is different from natural intelligence because it is artificial and rule-based, while human intelligence is biological, emotional, and adaptive.

(b) Describe the Turing Test for intelligence

The Turing Test, proposed by Alan Turing, evaluates a machine’s ability to exhibit intelligent behavior indistinguishable from a human. If a human evaluator cannot distinguish between responses from a human and a machine, the machine is said to have passed the test.

(c) Differentiate between uninformed search and informed search

Uninformed Search	Informed Search
No heuristic knowledge	Uses heuristic information
Blind exploration	Guided search
Example: BFS, DFS	Example: A*, Greedy

(d) Tic-Tac-Toe game tree (conceptual answer)

A game tree starts from the initial empty board (root node). Each level represents a player’s move (MAX or MIN). Leaf nodes represent win, lose, or draw states.
( In exam, draw a small game tree showing moves till win/lose)

(e) Concept of Unification in AI

Unification is the process of making two logical expressions identical by finding suitable substitutions for variables. It is widely used in first-order logic and Prolog.

(f) General syntax for a Prolog program

fact. rule :- condition. query ?

Example:

parent(john, mary). father(X, Y) :- parent(X, Y), male(X).

(g) Define speech act theory and find speech act

Speech act theory explains how language is used to perform actions.

Given: Performative = request Content = “the door is closed”

Speech act: Requesting someone to close the door.

(h) Reactive agent vs deliberative agent

Reactive Agent	Deliberative Agent
Responds instantly	Plans before acting
No internal model	Uses internal world model
Simple	Complex

(i) Applications of Artificial Intelligence

AI is used in expert systems, robotics, healthcare, self-driving cars, natural language processing, speech recognition, recommendation systems, and gaming.

(j) Concept of Information Retrieval

Information Retrieval (IR) deals with searching and retrieving relevant information from large datasets such as search engines, document repositories, and digital libraries.

SECTION B

Attempt any THREE (10 × 3 = 30 Marks)

(a) PEAS and task environment for automated car driving system

PEAS:

Performance: Safety, speed, fuel efficiency Environment: Roads, traffic, pedestrians

Actuators: Steering, brakes, accelerator Sensors: Cameras, radar, GPS

Properties:
Partially observable, stochastic, dynamic, continuous, multi-agent.

(b)

(i) Hill Climbing search technique

Hill climbing is a local search algorithm that moves toward the best neighboring state.
Drawbacks:

Local maxima Plateau Ridge problem

( Draw graph showing local maxima)

(ii) Constraint Satisfaction Problem – Cryptarithmetic

CSP involves variables, domains, and constraints.
For

CROSS + ROADS = DANGER

Each letter is assigned a unique digit, satisfying arithmetic constraints. Backtracking and constraint propagation are used.

(c) Convert sentences into First Order Logic (FOL)

Everyone is loyal to someone ∀x ∃y Loyal(x, y)

All Romans were loyal to Caesar or hated him ∀x Roman(x) → [Loyal(x, Caesar) ∨ Hates(x, Caesar)]

You can fool all of the people some of the time ∀x ∃t Fool(x, t)

No purple mushroom is poisonous ∀x [Purple(x) ∧ Mushroom(x)] → ¬Poisonous(x)

Everyone has a heart ∀x HasHeart(x)

(d) Types of Agent Communication Language (ACL)

KQML (Knowledge Query and Manipulation Language) – Used for knowledge exchange.

FIPA-ACL – Standard language for multi-agent communication with performatives like request, inform, propose.

(e) Role of AI

(i) Machine Translation: Converts text from one language to another using NLP.
(ii) Speech Recognition: Converts spoken language into text using AI models.

SECTION C

Q3

(a) Water Jug Problem and solution

The water jug problem involves measuring a specific quantity of water using two jugs of known capacities.

Solution:
Use state-space representation and operators such as fill, empty, and pour until the goal state is achieved.

(b) Intelligent Agents and types

An intelligent agent perceives its environment through sensors and acts using actuators to achieve goals.

Types:

Simple reflex agent Model-based agent

Goal-based agent Utility-based agent

Learning agent

Q4

(a) A* search algorithm A* uses evaluation function:
f(n) = g(n) + h(n)

It is complete and optimal if heuristic is admissible.
Example: Pathfinding in maps.

(b) Alpha-Beta pruning

Alpha-beta pruning reduces the number of nodes evaluated in MIN-MAX by eliminating branches that cannot affect final decision.

Q5

(a) Knowledge-based agent

A knowledge-based agent uses a knowledge base and inference engine to make decisions.
The inference engine derives new facts, enabling learning and reasoning.
( Draw KB + inference engine diagram)