1
QUESTION BANK
Name of the Department : EEE & MECH
Subject Code & Name : OCS351 &Artificial Intelligence and Machine Learning
Fundamentals
Year & Semester : IV & VII
UNIT I INTELLIGENT AGENT AND UNINFORMED SEARCH
PART-A
1. What is Artificial Intelligence (AI)?
Artificial Intelligence (AI) is the field of computer science dedicated to creating systems capable of performing
tasks that require human intelligence, such as learning, reasoning, problem-solving, and understanding natural
language.
2. What are the main foundations of AI?
The main foundations of AI include machine learning, neural networks, natural language processing, robotics,
and cognitive computing, which collectively enable machines to mimic and enhance human cognitive functions.
3. What was a significant milestone in the history of AI?
A significant milestone in AI history was the development of the first AI program by Alan Turing in the 1950s,
which laid the groundwork for future AI research and the concept of machine learning.
4. What is a current state-of-the-art application of AI?
A current state-of-the-art application of AI is deep learning, which powers advanced technologies such as
autonomous vehicles, facial recognition systems, and language translation services.
5. Name one benefit and one risk associated with AI.
A benefit of AI is its ability to automate complex tasks, leading to increased efficiency and productivity. A risk
is the potential for job displacement as AI systems can replace human labor in various industries.
6. What is an intelligent agent in AI?
An intelligent agent is an entity that perceives its environment through sensors and acts upon it using actuators
to achieve specific goals or tasks, often incorporating learning and adaptation capabilities.
7. How is the environment classified in the context of AI agents?
Department of EEE & MECH
,The environment for AI agents can be classified as either static or dynamic, depending on whether it changes while
the agent is operating, and as either deterministic or stochastic, depending on whether outcomes ar2e
predictable or random.
8. What are the primary components of an intelligent agent?
The primary components of an intelligent agent include sensors (to perceive the environment), actuators (to act
upon the environment), and a decision-making process (to determine actions based on perceptions).
9. What is the role of problem-solving agents in AI?
Problem-solving agents are designed to find solutions to problems by searching through possible actions and
states to achieve specific goals or objectives.
10. What is involved in formulating a problem in AI?
Formulating a problem involves defining the initial state, goal state, and the actions that can be taken to transform
the initial state into the goal state, often represented using state-space models.
11. What is uninformed search in AI?
Uninformed search, also known as blind search, refers to search strategies that explore the search space without any
domain-specific knowledge, such as Breadth-First Search or Depth-First Search.
12. What is Breadth-First Search (BFS) in AI?
Breadth-First Search (BFS) is an uninformed search algorithm that explores all nodes at the present depth level
before moving on to nodes at the next depth level, ensuring the shortest path in an unweighted graph.
13. How does Dijkstra's algorithm work?
Dijkstra's algorithm finds the shortest path from a starting node to all other nodes in a weighted graph by iteratively
selecting the node with the smallest known distance and updating the distances to its neighbors.
14. What is Depth-First Search (DFS) in AI?
Depth-First Search (DFS) is an uninformed search algorithm that explores as far down a branch as possible
before backtracking, using a stack to keep track of the nodes.
15. What is Depth-Limited Search (DLS)?
Depth-Limited Search (DLS) is a variant of Depth-First Search (DFS) that limits the depth of exploration to
avoid infinite loops in graphs with cycles, ensuring that the search does not exceed a predetermined depth limit.
16. How does the nature of the environment affect an AI agent's decision-making?
Department of EEE & MECH
, The nature of the environment affects an AI agent’s decision-making by determining how predictable or
unpredictable the environment is. For example, a static environment remains unchanged while the agent is act3ing,
making planning simpler, whereas a dynamic environment requires the agent to continually adapt to changes.
17. What are the main components of an AI agent's structure?
The main components of an AI agent’s structure include sensors (to perceive the environment), actuators (to
perform actions), and a decision-making system (to choose actions based on perceptions and goals).
18. What is the primary goal of a problem-solving agent in AI?
The primary goal of a problem-solving agent is to identify a sequence of actions that lead from an initial state to a
goal state, effectively solving a problem by exploring possible solutions and selecting the best one.
19. What are the key elements involved in formulating a problem for an AI agent?
Key elements in formulating a problem include defining the initial state, the goal state, and the actions that can be
taken to transition from the initial state to the goal state, often represented using a state-space model.
20. How does Uniform-Cost Search differ from Breadth-First Search?
Uniform-Cost Search differs from Breadth-First Search in that it takes the path cost into account and expands the
least-cost path first, while Breadth-First Search only considers the depth level of nodes and does not account for
varying path costs.
PART-B
1. Assess the risks and benefits of AI technologies in various sectors, such as healthcare and finance. How can
intelligent agents be designed to mitigate risks while maximizing benefits in these environments?
2. Analyze the historical developments in AI and evaluate how they have shaped the current state of the art in
artificial intelligence. What implications do these advancements have for future AI applications?
3. Evaluate the effectiveness of different search algorithms in solving complex problems. What factors
influence their performance in various environments?
4. Design an intelligent agent that can adapt to a dynamic environment. What structural components and
problem-solving strategies would you incorporate to ensure its effectiveness?
5. Analyze the implications of formulating problems effectively in the context of intelligent agents. How does
the clarity of problem formulation impact the efficiency of uninformed search strategies?
6. Analyze the advantages and disadvantages of Depth First Search (DFS) compared to Depth Limited Search
(DLS) in the context of problem-solving in AI. In what scenarios would one algorithm be preferred over the
other?
Department of EEE & MECH
QUESTION BANK
Name of the Department : EEE & MECH
Subject Code & Name : OCS351 &Artificial Intelligence and Machine Learning
Fundamentals
Year & Semester : IV & VII
UNIT I INTELLIGENT AGENT AND UNINFORMED SEARCH
PART-A
1. What is Artificial Intelligence (AI)?
Artificial Intelligence (AI) is the field of computer science dedicated to creating systems capable of performing
tasks that require human intelligence, such as learning, reasoning, problem-solving, and understanding natural
language.
2. What are the main foundations of AI?
The main foundations of AI include machine learning, neural networks, natural language processing, robotics,
and cognitive computing, which collectively enable machines to mimic and enhance human cognitive functions.
3. What was a significant milestone in the history of AI?
A significant milestone in AI history was the development of the first AI program by Alan Turing in the 1950s,
which laid the groundwork for future AI research and the concept of machine learning.
4. What is a current state-of-the-art application of AI?
A current state-of-the-art application of AI is deep learning, which powers advanced technologies such as
autonomous vehicles, facial recognition systems, and language translation services.
5. Name one benefit and one risk associated with AI.
A benefit of AI is its ability to automate complex tasks, leading to increased efficiency and productivity. A risk
is the potential for job displacement as AI systems can replace human labor in various industries.
6. What is an intelligent agent in AI?
An intelligent agent is an entity that perceives its environment through sensors and acts upon it using actuators
to achieve specific goals or tasks, often incorporating learning and adaptation capabilities.
7. How is the environment classified in the context of AI agents?
Department of EEE & MECH
,The environment for AI agents can be classified as either static or dynamic, depending on whether it changes while
the agent is operating, and as either deterministic or stochastic, depending on whether outcomes ar2e
predictable or random.
8. What are the primary components of an intelligent agent?
The primary components of an intelligent agent include sensors (to perceive the environment), actuators (to act
upon the environment), and a decision-making process (to determine actions based on perceptions).
9. What is the role of problem-solving agents in AI?
Problem-solving agents are designed to find solutions to problems by searching through possible actions and
states to achieve specific goals or objectives.
10. What is involved in formulating a problem in AI?
Formulating a problem involves defining the initial state, goal state, and the actions that can be taken to transform
the initial state into the goal state, often represented using state-space models.
11. What is uninformed search in AI?
Uninformed search, also known as blind search, refers to search strategies that explore the search space without any
domain-specific knowledge, such as Breadth-First Search or Depth-First Search.
12. What is Breadth-First Search (BFS) in AI?
Breadth-First Search (BFS) is an uninformed search algorithm that explores all nodes at the present depth level
before moving on to nodes at the next depth level, ensuring the shortest path in an unweighted graph.
13. How does Dijkstra's algorithm work?
Dijkstra's algorithm finds the shortest path from a starting node to all other nodes in a weighted graph by iteratively
selecting the node with the smallest known distance and updating the distances to its neighbors.
14. What is Depth-First Search (DFS) in AI?
Depth-First Search (DFS) is an uninformed search algorithm that explores as far down a branch as possible
before backtracking, using a stack to keep track of the nodes.
15. What is Depth-Limited Search (DLS)?
Depth-Limited Search (DLS) is a variant of Depth-First Search (DFS) that limits the depth of exploration to
avoid infinite loops in graphs with cycles, ensuring that the search does not exceed a predetermined depth limit.
16. How does the nature of the environment affect an AI agent's decision-making?
Department of EEE & MECH
, The nature of the environment affects an AI agent’s decision-making by determining how predictable or
unpredictable the environment is. For example, a static environment remains unchanged while the agent is act3ing,
making planning simpler, whereas a dynamic environment requires the agent to continually adapt to changes.
17. What are the main components of an AI agent's structure?
The main components of an AI agent’s structure include sensors (to perceive the environment), actuators (to
perform actions), and a decision-making system (to choose actions based on perceptions and goals).
18. What is the primary goal of a problem-solving agent in AI?
The primary goal of a problem-solving agent is to identify a sequence of actions that lead from an initial state to a
goal state, effectively solving a problem by exploring possible solutions and selecting the best one.
19. What are the key elements involved in formulating a problem for an AI agent?
Key elements in formulating a problem include defining the initial state, the goal state, and the actions that can be
taken to transition from the initial state to the goal state, often represented using a state-space model.
20. How does Uniform-Cost Search differ from Breadth-First Search?
Uniform-Cost Search differs from Breadth-First Search in that it takes the path cost into account and expands the
least-cost path first, while Breadth-First Search only considers the depth level of nodes and does not account for
varying path costs.
PART-B
1. Assess the risks and benefits of AI technologies in various sectors, such as healthcare and finance. How can
intelligent agents be designed to mitigate risks while maximizing benefits in these environments?
2. Analyze the historical developments in AI and evaluate how they have shaped the current state of the art in
artificial intelligence. What implications do these advancements have for future AI applications?
3. Evaluate the effectiveness of different search algorithms in solving complex problems. What factors
influence their performance in various environments?
4. Design an intelligent agent that can adapt to a dynamic environment. What structural components and
problem-solving strategies would you incorporate to ensure its effectiveness?
5. Analyze the implications of formulating problems effectively in the context of intelligent agents. How does
the clarity of problem formulation impact the efficiency of uninformed search strategies?
6. Analyze the advantages and disadvantages of Depth First Search (DFS) compared to Depth Limited Search
(DLS) in the context of problem-solving in AI. In what scenarios would one algorithm be preferred over the
other?
Department of EEE & MECH
