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  • April 13, 2023
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  • 2022/2023
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SS21 exam solution


Grundlagen der Künstlichen Intelligenz (IN2062) (Technische Universität München)




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Chair of Robotics, Artificial Intelligence and Real-time Systems
Department of Informatics
Technical University of Munich




Note:
Ecorrection • During the attendance check a sticker containing a unique code will be put on this exam.
Place student sticker here • This code contains a unique number that associates this exam with your registration number.
• This number is printed both next to the code and to the signature field in the attendance check list.




Grundlagen der künstlichen Intelligenz




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Exam: IN2062 / Endterm Date: Monday 1st March, 2021
Examiner: Prof. Dr.-Ing. Matthias Althoff Time: 18:15 – 19:45




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P1 P2 P3 P4 P5 P6 P7 P8 P9 P 10

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Working instructions
• This exam consists of 18 pages with a total of 10 problems.
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Please make sure that you received a complete copy of the exam.
• The total amount of achievable credits in this exam is 61.5 credits.
• Detaching pages from the exam is prohibited.
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• Allowed resources:
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– a pen or PDF editor (do not write with red or green colors nor use pencils)
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– a non-programmable pocket calculator
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– the provided formula sheet
– empty scratch paper (do not submit)
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• Please write answers on the exam booklet only. If you run out of space, write on the additional pages provided.
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Notes on other paper will be disregarded.
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• You must hand in all pages of the exam.
• Answers are only accepted if the solution approach is documented. Give a reason for each answer
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unless explicitly stated otherwise in the respective subproblem.
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• All subproblems are solvable independently from each other if not explicitly stated differently.
• Multiple-Choice questions are evaluated automatically. Use a cross to select your answer:
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⇤ Answer A
⇥ Answer B

If you want to correct your answer, fill out the checkbox, and cross your new answer:
⇥ Answer A
⌅ Answer B
Notes next to the checkboxes cannot be evaluated.


Left room from to / Early submission at

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Problem 1 Search (10.5 credits)
In the following tasks we search for a path from node A to node G , if not stated otherwise. If multiple nodes can be
explored next, alphabetic ordering should be used as the tie breaker, e.g., if B and C are added to the frontier, B is
added first.
On each of the following graphs we apply breadth-first (BFS) and depth-first (DFS) Graph-Search. Find out which
graphs are explored by each algorithm in the order A , B , C , D .

1 2 3

A B A B A B




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C D C D C D




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E G E G E G

a) Tick all graphs that are explored in the order A , B , C , D by BFS:

×1 ×2

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b) Tick all graphs that are explored in the order A , B , C , D by DFS:

×3 ×2
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0 c) Name another uninformed search algorithm that explores the nodes in graph 1 in the same order as BFS:

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Iterative Deepening Search, Uniform-cost search / Dijktstra with unitary cost
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d) Does Depth-First Tree-Search terminate for graph 2 (0.5 points)?
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Yes × No
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0 e) State the first four nodes visited by DFS Tree-Search searching from A to G on graph 2.
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A - right neighbor - A - right neighbor
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