Contents

- 1 What is the minimum remaining values heuristic?
- 2 What does the minimum remaining values MRV heuristic do?
- 3 Why it is a good heuristic to choose the variable that is most constrained but the value that is least constraining in a CSP search?
- 4 What is a unary constraint?
- 5 Which is used to improve the performance of heuristic search?
- 6 What is main criteria to solve CSP?
- 7 How is the minimum remaining value heuristic used?
- 8 Which is the best use of a heuristic?
- 9 How are heuristics used in constraint satisfaction problems?
- 10 When is the heuristic h ( n ) called admissible?

## What is the minimum remaining values heuristic?

Minimum remaining values (MRV): choose the variable with the fewest possible values. Least-constraining value heuristic: choose a value that rules out the smallest number of values in variables connected to the current variable by constraints.

## What does the minimum remaining values MRV heuristic do?

T The minimum-remaining-values (MRV) heuristic chooses the variable with the fewest remaining legal values to assign next. 2j. T The least-constraining-value heuristic prefers the value that rules out the fewest choices for the neighboring variables in the constraint graph.

## Why it is a good heuristic to choose the variable that is most constrained but the value that is least constraining in a CSP search?

It is a good heuristic to choose the variable that is most constrained because such variables are likely to cause a failure, and it is more efficient to fail as early as possible. The least constraining value heuristic is good because it allows the most chances for future assignments thus avoiding conflict.

## What is a unary constraint?

A unary constraint is a constraint on a single variable (e.g., X≠4). A binary constraint is a constraint over a pair of variables (e.g., X≠Y). A possible world w satisfies a set of constraints if, for every constraint, the values assigned in w to the variables in the scope of the constraint satisfy the constraint.

## Which is used to improve the performance of heuristic search?

9. Which is used to improve the performance of heuristic search? Explanation: Good heuristic can be constructed by relaxing the problem, So the performance of heuristic search can be improved.

## What is main criteria to solve CSP?

To solve a CSP, design the variable, domain and constraints set. Then, look for an optimal solution. The optimal solution should satisfy all constraints.

## How is the minimum remaining value heuristic used?

Degree heuristic:assign a value to the variable that is involved in the largest number of constraints on other unassigned variables. Minimum remaining values (MRV):choose the variable with the fewestpossible values.

## Which is the best use of a heuristic?

(in node expansion? hill-climbing ?) • Best-first: – select the best from allthe nodes encountered so far in OPEN. – “good” use heuristics • Heuristic estimates value of a node – promise of a node – difficulty of solving the subproblem – quality of solution represented by node – the amount of information gained.

## How are heuristics used in constraint satisfaction problems?

In constraint satisfaction problems, heuristics can be used to improve the performance of a bactracking solver. Three commonly given heuristics for simple backtracking solvers are:

## When is the heuristic h ( n ) called admissible?

• The heuristic function h(n) is called admissible if h(n) is never larger than h*(n), namely h(n) is always less or equal to true cheapest cost from n to the goal. • A* is admissible if it uses an admissible heuristic, and h(goal) = 0.