Old Exam Part 1

Question 1

Above you see a simple crypto-arithmetic puzzle, and the corresponding (partial) constraint graph that shows all constraints except the one that
all numbers must be different. The left-most node is B, fill in the other three nodes 1., 2., and 3., analogous to the examples in the lecture.

Answer 1

The crypto-arithmetic puzzle involves finding distinct digits for each letter such that the equation is correct. Let’s break down the solution:

Given:

A B
+ D
——
A D

Constraint Dependencies:
A != B != D
B + D = D
X + A = A

	X is the carry-over - it can be 0 or 1 (because 9 + 9 = 18) 
	A can not be 0
	
3.	Final Mapping of Nodes:
*	Node 1: X
*	Node 2: A
*	Node 3: D

This fills in the nodes based on the puzzle structure.

Question 2

Map the following important contributions in the history of AI to their associated names.

George Boole, Aristotle, Charles Babbage, Kurt Gödel

• proved that any logical system powerful enough to formalize mathematics is either incomplete or
  inconsistent
• suggested an algebra for logic
• constructed the first programmable computer
• defined general patterns for logical reasoning

Answer 2

Die richtige Antwort ist:
→ Kurt Gödel,
→ George Boole,
→ Charles Babbage,
→ Aristotle

Question 3

Which of the following general heuristics for constraint solving does not aim at selecting a variable:

Wählen Sie eine Antwort:

a. Minimum Remaining Values Heuristic
b. Min-Conflicts Heuristics
c. Degree Heuristics
d. Least Constraining Value Heuristic

Answer 3

Die richtige Antwort ist:
d. Least Constraining Value Heuristic

Question 4

Specify whether the following statements are true or false:

1. Machine Learning is an essential part of every AI system, because an agent that does not learn cannot be considered to be an Artificial Intelligence.
2. Alan Turing coined the term ”Artificial Intelligence” in 1956 at the Dartmouth Conference.
3. At the heart of genetic algorithms is an operator called cross-over, which combines parts of two solutions into a new solution.

Answer 4

1. Machine Learning is an essential part of every AI system, because an agent that does not learn cannot be considered to be an Artificial Intelligence. –> False
2. Alan Turing coined the term ”Artificial Intelligence” in 1956 at the Dartmouth Conference. –> False
3. At the heart of genetic algorithms is an operator called cross-over, which combines parts of two solutions into a new solution. –> True

Question 5

Map the following textbook definitions of artificial intelligence to the corresponding point of view they advocate:

• Systems that think like humans
• Systems that think rationally
• Systems that act like humans
• Systems that act rationally

”AI … is concerned with intelligent behavior in artifacts.” (Nilsson, 1998)

”The art of creating machines that perform functions that require intelligence when performed by
people.” (Kurzweil, 1990)

”The study of the computations that make it possible to perceive, reason, and act.” (Winston, 1992)

”The exciting new effort to make computers think … machines with minds, in the full and literal sense.”
(Haugeland, 1985)

Answer 5

Die richtige Antwort ist:

”AI … is concerned with intelligent behavior in artifacts.” (Nilsson, 1998) → Systems that act rationally,

”The art of creating machines that perform functions that require intelligence when performed by people.” (Kurzweil, 1990) → Systems that act
like humans,

”The study of the computations that make it possible to perceive, reason, and act.” (Winston, 1992) → Systems that think rationally,

”The exciting new effort to make computers think … machines with minds, in the full and literal sense.” (Haugeland, 1985) → Systems that think
like humans

Question 6

Which of the following techniques have we considered to be particularly useful for different steps when solving a Sudoku puzzle?

heuristics, constraint satisfaction, constraint propagation, backtracking search

• try out one of several possible values and possibly come back later if it doesn’t work out
• use the value that has been filled in for reducing the set of possible values in neighboring squares
• selecting the next square that could be filled in
• check which values can be filled in a selected square constraint satisfaction

Answer 6

• backtracking search
• constraint propagation
• heuristics
• constraint satisfaction

Die richtige Antwort ist:

• try out one of several possible values and possibly come back later if it doesn’t work out → backtracking search,
• use the value that has been filled in for reducing the set of possible values in neighboring squares → constraint propagation,
• selecting the next square that could be filled in → heuristics,
• check which values can be filled in a selected square → constraint satisfaction