Mastering Problem Solving Methods

What is an uninformed search strategy?

• A search strategy that uses heuristics to find solutions quickly.

• A search algorithm that relies on prior knowledge of the problem domain.

• An uninformed search strategy is a search algorithm that does not use any domain-specific knowledge to guide its search.

• A method that guarantees finding the optimal solution in all cases.

Give an example of an informed search strategy.

• A* search algorithm

• Random search

• Depth-first search

• Breadth-first search

How do heuristics improve problem-solving efficiency?

• Heuristics improve problem-solving efficiency by providing mental shortcuts that simplify decision-making.

• Heuristics are only useful in mathematical problems and not in real-life situations.

• Heuristics eliminate the need for any analysis in problem-solving.

• Heuristics slow down decision-making by complicating the process.

What is the main advantage of local search algorithms?

• They always find the optimal solution.

• They are efficient in finding satisfactory solutions quickly.

• They require less memory than other algorithms.

• They can solve any problem in constant time.

Define a constraint satisfaction problem (CSP).

• A CSP is a method for optimizing algorithms without constraints.

• A CSP is a programming language designed for constraint-based programming.

• A CSP is a type of data structure used for storing variables only.

• A CSP consists of variables, domains, and constraints, aiming to find a solution that satisfies all constraints.

What is the purpose of constraint propagation in CSPs?

• To increase the number of variables in the problem.

• To randomly assign values to variables.

• To eliminate all possible solutions immediately.

• To reduce the search space by enforcing constraints among variables.

Explain the backtracking search method.

• Backtracking search is a method that only explores the first possible configuration.

• Backtracking search is a technique that guarantees finding the optimal solution immediately.

• Backtracking search is a method for solving problems by exploring all possible configurations and backtracking when a constraint is violated.

• Backtracking search is a method that avoids exploring any configurations to save time.

How does alpha-beta pruning optimize game playing?

• Alpha-beta pruning is used to enhance the graphics of the game.

• Alpha-beta pruning increases the number of nodes evaluated in the minimax algorithm.

• Alpha-beta pruning optimizes game playing by reducing the number of nodes evaluated in the minimax algorithm.

• Alpha-beta pruning eliminates the need for a minimax algorithm altogether.

What distinguishes stochastic games from deterministic games?

• Stochastic games are played in a single round, while deterministic games are played over multiple rounds.

• Stochastic games include randomness in outcomes, while deterministic games do not.

• Stochastic games have fixed outcomes, while deterministic games vary.

• Deterministic games involve chance events, while stochastic games are predictable.

Describe a scenario where local search algorithms are preferred over global search methods.

• Local search algorithms are best for problems with no initial solution.

• Global search methods are always faster than local search algorithms.

• Local search algorithms guarantee finding the optimal solution every time.

• Local search algorithms are preferred for problems like the traveling salesman problem when a good initial solution is available.