Mumbai University Solved Question Papers
Artificial Intelligence
Previous Year Question Paper with Solution
BSc CS · Sem 5
2023-24 Examination
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BSc CS Sem 5 Artificial Intelligence 2023-24 Question Paper with Solutions
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First published on munotes.in on 17 October 2026.
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The University does not publish an official answer key for this paper. The answers in this volume are model answers, written to show how a full-mark answer is built. They are a study aid, not an authority on what an examiner marked.
The question paper reproduced here is the paper as set by the University of Mumbai at the 2023-24 examination.
Contents
The questions below are the paper as the University of Mumbai set it at the 2023-24 examination, in the order it was set.
MarksPage
MarksPage
The Paper as Set
The questions in this volume are the questions asked at the 2023-24 examination, reproduced as the University of Mumbai set them, in the order it set them. Nothing has been reworded, added or left out. Only the answers are ours. See the original question paper.
Duration 2½ hours · Total marks 75 · 24 questions answered
Instructions printed on the paper
- N.B. (1) All questions are compulsory. (2) Figures to the right indicate marks. (3) Illustrations, in-depth answers and diagrams will be appreciated. (4) Mixing of sub-questions is not allowed.
How to use this volume
Solve the paper first, under exam conditions and against the clock. Then read the answers here and mark your own. Reading a solution before attempting the question feels productive and teaches very little, because recognising an answer is not the same as being able to write one.
SECTION I
Q.1
Attempt ANY FOUR from the following · 20 Marks
(a)What is PEAS? Give a PEAS description for playing a tennis match and vacuum cleaner problem.[5]
Answer
For full marks, cover: the meaning of PEAS and its purpose, a complete PEAS table for a tennis-playing agent and for a robot vacuum cleaner, and the type of environment each faces.
PEAS
PEAS names the four elements that together specify an agent's task environment: Performance measure, Environment, Actuators and Sensors. Before an agent is built, the designer writes these down, because they decide what "behaving well" means and what the agent can perceive and do.
Tennis-playing agent (a robot player)
| Element | Tennis match |
|---|---|
| Performance measure | points, games and sets won; matches won; few faults and no rule violations |
| Environment | the court, net, ball, opponent, umpire, and conditions such as wind and light |
| Element | Tennis match |
|---|---|
| Actuators | arm and racket for hitting, legs or wheels for running, joints for serving |
| Sensors | cameras for tracking the ball and the opponent, joint and balance sensors, microphones for the umpire's call |
Its environment is multi-agent and competitive (the opponent tries to make it lose), dynamic (the ball moves while the agent thinks), continuous and only partially observable (it cannot see the opponent's intention).
Vacuum cleaner robot
| Element | Vacuum cleaner |
|---|---|
| Performance measure | amount of dirt cleaned, area covered, time and battery used, no damage to furniture, low noise |
| Environment | rooms, floor types (tile, carpet), furniture, stairs, dirt, people and pets |
| Actuators | wheels, side brushes, main brush, suction motor |
| Sensors | dirt sensor, bump sensor, cliff sensor (to avoid stairs), wall or infrared sensors, camera or lidar |
Its environment is partially observable (it senses only near itself), dynamic (people move furniture and spill things), and mostly single-agent.
Why the tables differ
The tennis agent must react in fractions of a second against an adversary, while the vacuum robot must cover space efficiently over a long time. Writing PEAS first makes these different demands visible.
Conclusion. PEAS (Performance measure, Environment, Actuators, Sensors) specifies an agent's task environment. A tennis agent aims to win points and matches on a court against an opponent, acting with a racket and legs and sensing with ball-tracking cameras. A vacuum robot aims to remove dirt efficiently in a house, acting with wheels, brushes and suction and sensing dirt, bumps and stairs.
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