Question 1

Define Artificial Intelligence.

Accepted Answer

Artificial Intelligence is the study and design of intelligent agents that perceive their environment and take actions that maximize their chances of success.

Question 2

What is a rational agent?

Accepted Answer

A rational agent is one that acts to achieve the best outcome or the best expected outcome when there is uncertainty.

Question 3

State the difference between blind search and heuristic search.

Accepted Answer

Blind search explores the state space without domain-specific knowledge, whereas heuristic search uses problem-specific knowledge to find solutions efficiently.

Question 4

Define admissible heuristic.

Accepted Answer

An admissible heuristic is an evaluation function that never overestimates the true cost to reach the goal from the current node.

Question 5

What is the Turing Test?

Accepted Answer

The Turing Test is a test of a machine's ability to exhibit intelligent behavior indistinguishable from that of a human.

Question 6

Explain the concept of Alpha-Beta pruning.

Accepted Answer

Alpha-Beta pruning is an optimization technique for the minimax algorithm that reduces the number of evaluated nodes by pruning branches that cannot influence the decision.

Question 7

What is First Order Logic (FOL)?

Accepted Answer

First Order Logic is a formal logical system that uses quantified variables over objects to express complex relationships.

Question 8

Define Forward Chaining.

Accepted Answer

Forward Chaining is a data-driven reasoning method that applies inference rules to known facts to extract more data until a goal is reached.

Question 9

What is an Expert System?

Accepted Answer

An Expert System is a computer program that emulates the decision-making ability of a human expert using a knowledge base and inference rules.

Question 10

State Bayes' Theorem.

Accepted Answer

Bayes' Theorem provides a way to calculate the probability of a hypothesis based on prior knowledge and new evidence.

Question 11

Explain the PEAS description for an automated taxi driver.

Accepted Answer

The PEAS description for an automated taxi driver involves Performance, Environment, Actuators, and Sensors specifically tailored for driving.

Question 12

Describe the A* search algorithm and its properties.

Accepted Answer

A* search is an optimal and complete informed search algorithm that uses both path cost and heuristic estimates to find the shortest path.

Question 13

Explain the Minimax algorithm with an example.

Accepted Answer

The Minimax algorithm is a decision-making strategy in two-player zero-sum games where players try to maximize their score while minimizing the opponent's.

Question 14

Convert the following sentence into First Order Logic: "Every student who tak…

Accepted Answer

The sentence is converted using the universal quantifier and implications representing Student, Takes, and Passes predicates.

Question 15

Differentiate between Propositional Logic and First Order Logic.

Accepted Answer

Propositional logic uses simple factual statements, while First Order logic uses objects, predicates, and quantifiers for richer representation.

Question 16

Explain the architecture of a typical Expert System.

Accepted Answer

A typical Expert System comprises a Knowledge Base, an Inference Engine, and a User Interface.

Question 17

Discuss the components of a Natural Language Processing system.

Accepted Answer

An NLP system processes language through multiple stages: Lexical, Syntactic, Semantic, Discourse, and Pragmatic analysis.

Question 18

Explain the various types of Intelligent Agents with their block diagrams.

Accepted Answer

Intelligent Agents are categorized into Simple Reflex, Model-Based, Goal-Based, and Utility-Based agents, each with increasing complexity.

Question 19

Solve the 8-puzzle problem using Hill Climbing search. Explain the algorithm …

Accepted Answer

Hill Climbing is a local search algorithm that can be applied to the 8-puzzle problem, but it suffers from local maxima, ridges, and plateau issues.

Question 20

Describe the Constraint Satisfaction Problem (CSP) with the help of the Map C…

Accepted Answer

A Constraint Satisfaction Problem involves assigning values to variables subject to constraints, perfectly illustrated by the Map Coloring problem.

Question 21

Explain the conceptual dependency and semantic networks for knowledge represe…

Accepted Answer

Conceptual Dependency and Semantic Networks are graphical knowledge representation frameworks used to depict the meaning of sentences and relationships between concepts.

Question 22

Explain Bayesian Networks. Construct a Bayesian network for a medical diagnos…

Accepted Answer

Bayesian Networks are probabilistic graphical models representing variables and their conditional dependencies via a directed acyclic graph.

Principles of Artificial Intelligence