ARTIFICIAL INTELLIGENCE A MODERN
APPROACH EXAM 2026 FINAL EXAM PAPER
FULL QUESTIONS AND COMPLETE ANSWERS
◉ Intelligent Agent. Answer: Entity that perceives environment and
acts accordingly.
◉ Percepts. Answer: Data received from the environment by agents.
◉ Actions. Answer: Responses performed by agents based on
percepts.
◉ Utility. Answer: Measure of satisfaction or benefit from actions.
◉ Machine Learning. Answer: AI subfield focusing on learning from
data.
◉ Deep Learning. Answer: Subset of machine learning using neural
networks.
◉ Probabilistic Programming. Answer: Programming paradigm for
uncertain data modeling.
,◉ Multiagent Systems. Answer: Systems with multiple interacting
intelligent agents.
◉ Reinforcement Learning. Answer: Learning through trial and
error for optimal actions.
◉ Natural Language Understanding. Answer: AI's ability to
comprehend human language.
◉ Computer Vision. Answer: Field enabling machines to interpret
visual data.
◉ Robotics. Answer: Branch of AI focused on robot design and
function.
◉ Ethics in AI. Answer: Study of moral implications of AI
technologies.
◉ Fairness in AI. Answer: Ensuring unbiased outcomes in AI
systems.
◉ Trust in AI. Answer: User confidence in AI system reliability.
,◉ Safety in AI. Answer: Preventing harm caused by AI systems.
◉ Algorithms. Answer: Step-by-step procedures for calculations or
problem-solving.
◉ Data Structures. Answer: Organized formats for storing and
managing data.
◉ Complexity. Answer: Study of resource usage in algorithms.
◉ Appendix A. Answer: Contains mathematical concepts and
notation.
◉ Appendix B. Answer: Describes pseudocode used in the book.
◉ ISBN. Answer: International Standard Book Number for
identification.
◉ Bibliography. Answer: List of sources referenced in the book.
◉ Index. Answer: Alphabetical listing of topics covered in the book.
, ◉ Online Resources. Answer: Additional materials available for
study and practice.
◉ Exercises. Answer: Practice problems to reinforce learning
concepts.
◉ Programming Projects. Answer: Hands-on coding tasks related to
AI topics.
◉ Research Projects. Answer: In-depth investigations into specific AI
areas.
◉ Online resources. Answer: Available at pearsonhighered.com/cs-
resources and aima.cs.berkeley.edu.
◉ Programming projects. Answer: Implementations available in
Python, Java, and more.
◉ Research projects. Answer: Additional projects related to the
book's content.
◉ 1400 schools list. Answer: Includes links to course materials and
syllabi.
APPROACH EXAM 2026 FINAL EXAM PAPER
FULL QUESTIONS AND COMPLETE ANSWERS
◉ Intelligent Agent. Answer: Entity that perceives environment and
acts accordingly.
◉ Percepts. Answer: Data received from the environment by agents.
◉ Actions. Answer: Responses performed by agents based on
percepts.
◉ Utility. Answer: Measure of satisfaction or benefit from actions.
◉ Machine Learning. Answer: AI subfield focusing on learning from
data.
◉ Deep Learning. Answer: Subset of machine learning using neural
networks.
◉ Probabilistic Programming. Answer: Programming paradigm for
uncertain data modeling.
,◉ Multiagent Systems. Answer: Systems with multiple interacting
intelligent agents.
◉ Reinforcement Learning. Answer: Learning through trial and
error for optimal actions.
◉ Natural Language Understanding. Answer: AI's ability to
comprehend human language.
◉ Computer Vision. Answer: Field enabling machines to interpret
visual data.
◉ Robotics. Answer: Branch of AI focused on robot design and
function.
◉ Ethics in AI. Answer: Study of moral implications of AI
technologies.
◉ Fairness in AI. Answer: Ensuring unbiased outcomes in AI
systems.
◉ Trust in AI. Answer: User confidence in AI system reliability.
,◉ Safety in AI. Answer: Preventing harm caused by AI systems.
◉ Algorithms. Answer: Step-by-step procedures for calculations or
problem-solving.
◉ Data Structures. Answer: Organized formats for storing and
managing data.
◉ Complexity. Answer: Study of resource usage in algorithms.
◉ Appendix A. Answer: Contains mathematical concepts and
notation.
◉ Appendix B. Answer: Describes pseudocode used in the book.
◉ ISBN. Answer: International Standard Book Number for
identification.
◉ Bibliography. Answer: List of sources referenced in the book.
◉ Index. Answer: Alphabetical listing of topics covered in the book.
, ◉ Online Resources. Answer: Additional materials available for
study and practice.
◉ Exercises. Answer: Practice problems to reinforce learning
concepts.
◉ Programming Projects. Answer: Hands-on coding tasks related to
AI topics.
◉ Research Projects. Answer: In-depth investigations into specific AI
areas.
◉ Online resources. Answer: Available at pearsonhighered.com/cs-
resources and aima.cs.berkeley.edu.
◉ Programming projects. Answer: Implementations available in
Python, Java, and more.
◉ Research projects. Answer: Additional projects related to the
book's content.
◉ 1400 schools list. Answer: Includes links to course materials and
syllabi.
