2.2.2 Computational methods

What makes a problem solvable by computational methods?

• It can be expressed as a sequence of logical steps

• It is easy to solve mentally

• It is based on real-world ambiguity

• It requires emotional intelligence

What is problem recognition in computational methods?

• Identifying that a problem exists and can be tackled computationally

• Ignoring issues until they disappear

• Waiting for errors to appear

• Using intuition only

What is problem decomposition?

• Breaking a complex problem into smaller, manageable parts

• Combining problems into one

• Making the problem harder

• Ignoring parts of the problem

What is the divide and conquer approach?

• Dividing a problem into sub-problems and solving them recursively

• Combining solutions from different problems

• Using trial and error

• Avoiding recursion entirely

What is the role of abstraction in computational methods?

• To hide unnecessary details and focus on the core problem

• To solve problems manually

• To draw graphics

• To encrypt data

What is backtracking used for?

• Finding a solution by trying options and undoing steps when necessary

• Storing all previous versions of a file

• Visualizing outputs only

• Looping indefinitely

Which problem is best suited for backtracking?

• Maze-solving

• Sorting numbers

• Basic arithmetic

• Data conversion

What is data mining?

• Extracting useful patterns from large datasets

• Digging tunnels with robots

• Deleting irrelevant data

• Backing up data

What is the purpose of heuristics?

• To find good-enough solutions when optimal ones are too costly to compute

• To ensure exact answers always

• To guarantee the best result

• To delay decisions

Which technique is commonly used in artificial intelligence for decision making?

• Heuristics

• Binary search

• String concatenation

• Loop unrolling