(SEM VII) THEORY EXAMINATION 2022-23 ARTIFICIAL INTELLIGENCE

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

(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

(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)

(b) Robert is criminal – forward chaining

Facts and rules are applied step-by-step.
Since Robert is American and sold missiles to an enemy nation, inference proves that Robert is a criminal.

Q6

(a) Contract Net Protocol

It is a task allocation protocol for multi-agent systems.

Stages:                                                                           Announcement

Bidding                                                                            Awarding

Execution

(b) Multi-agent concepts (Any two)

Argument: Logical justification of beliefs               Negotiation: Agents reach mutual agreement

Bargaining: Compromise between agents

Q7

(a) Role of NLP in AI                                                NLP enables machines to understand human language.

Stages:
Lexical → Syntax → Semantics → Discourse → Pragmatics

(b) Robotics and AI

Robotics involves designing intelligent machines.

Components: Sensors, actuators, controller, power unit.
Computer vision enables robots to perceive and interpret visual information.