Page |1
Artificial Intelligence: A Modern Approach
Overview Questions and Correct Answers/
Latest Update / Already Graded
Artificial Intelligence (AI)
Ans: Field focused on intelligent agents and learning.
Intelligent Agent
Ans: Entity that perceives environment and acts accordingly .
Percepts
Ans: Data received from the environment by agents.
Actions
Ans: Responses performed by agents based on percepts.
Utility
Ans: Measure of satisfaction or benefit from actions.
Machine Learning
All rights reserved © 2025/ 2026 |
, Page |2
Ans: AI subfield focusing on learning from data.
Deep Learning
Ans: Subset of machine learning using neural networks.
Probabilistic Programming
Ans: Programming paradigm for uncertain data modeling.
Multiagent Systems
Ans: Systems with multiple interacting intelligent agents.
Reinforcement Learning
Ans: Learning through trial and error for optimal actions.
Natural Language Understanding
Ans: AI's ability to comprehend human language.
Computer Vision
Ans: Field enabling machines to interpret visual data.
All rights reserved © 2025/ 2026 |
, Page |3
Robotics
Ans: Branch of AI focused on robot design and function.
Ethics in AI
Ans: Study of moral implications of AI technologies.
Fairness in AI
Ans: Ensuring unbiased outcomes in AI systems.
Trust in AI
Ans: User confidence in AI system reliability.
Safety in AI
Ans: Preventing harm caused by AI systems.
Algorithms
Ans: Step-by-step procedures for calculations or problem-
solving.
All rights reserved © 2025/ 2026 |
, Page |4
Data Structures
Ans: Organized formats for storing and managing data.
Complexity
Ans: Study of resource usage in algorithms.
Appendix A
Ans: Contains mathematical concepts and notation.
Appendix B
Ans: Describes pseudocode used in the book.
ISBN
Ans: International Standard Book Number for identification.
Bibliography
Ans: List of sources referenced in the book.
All rights reserved © 2025/ 2026 |
Artificial Intelligence: A Modern Approach
Overview Questions and Correct Answers/
Latest Update / Already Graded
Artificial Intelligence (AI)
Ans: Field focused on intelligent agents and learning.
Intelligent Agent
Ans: Entity that perceives environment and acts accordingly .
Percepts
Ans: Data received from the environment by agents.
Actions
Ans: Responses performed by agents based on percepts.
Utility
Ans: Measure of satisfaction or benefit from actions.
Machine Learning
All rights reserved © 2025/ 2026 |
, Page |2
Ans: AI subfield focusing on learning from data.
Deep Learning
Ans: Subset of machine learning using neural networks.
Probabilistic Programming
Ans: Programming paradigm for uncertain data modeling.
Multiagent Systems
Ans: Systems with multiple interacting intelligent agents.
Reinforcement Learning
Ans: Learning through trial and error for optimal actions.
Natural Language Understanding
Ans: AI's ability to comprehend human language.
Computer Vision
Ans: Field enabling machines to interpret visual data.
All rights reserved © 2025/ 2026 |
, Page |3
Robotics
Ans: Branch of AI focused on robot design and function.
Ethics in AI
Ans: Study of moral implications of AI technologies.
Fairness in AI
Ans: Ensuring unbiased outcomes in AI systems.
Trust in AI
Ans: User confidence in AI system reliability.
Safety in AI
Ans: Preventing harm caused by AI systems.
Algorithms
Ans: Step-by-step procedures for calculations or problem-
solving.
All rights reserved © 2025/ 2026 |
, Page |4
Data Structures
Ans: Organized formats for storing and managing data.
Complexity
Ans: Study of resource usage in algorithms.
Appendix A
Ans: Contains mathematical concepts and notation.
Appendix B
Ans: Describes pseudocode used in the book.
ISBN
Ans: International Standard Book Number for identification.
Bibliography
Ans: List of sources referenced in the book.
All rights reserved © 2025/ 2026 |
