Contents

- 1 Can a heuristic be not admissible and consistent?
- 2 Is the heuristic admissible Why or why not?
- 3 Is 0 heuristic admissible?
- 4 Is 0 A consistent heuristic?
- 5 What is difference between admissible and consistent heuristic?
- 6 Can a heuristic be zero?
- 7 When is a heuristic considered to be admissible?
- 8 When is a heuristic consistent with an estimated cost?

## Can a heuristic be not admissible and consistent?

Notes. While all consistent heuristics are admissible, not all admissible heuristics are consistent. For tree search problems, if an admissible heuristic is used, the A* search algorithm will never return a suboptimal goal node.

**What if the heuristic is not admissible?**

A non-admissible heuristic may overestimate the cost of reaching the goal. It may or may not result in an optimal solution. Thus, the total cost (= search cost + path cost) may actually be lower than an optimal solution using an admissible heuristic.

### Is the heuristic admissible Why or why not?

A heuristic function is admissible if the estimated cost is never more than the actual cost from the current node to the goal node.

**Does admissible imply consistent?**

(c) Prove that if a heuristic is consistent, it must be admissible. We can prove that consistency implies admissibility through induction. Recall that consistency is defined such that h(n) ≤ c(n, n + 1) + h(n + 1).

#### Is 0 heuristic admissible?

When we use A* with a non admissible heuristic we can sometimes get a non optimal path as result. But when it is allowed to have path with zero cost, the only admissible heuristic that comes to my mind is h(x) = 0 , which turns A* into a “simple” Dijkstra’s algorithm.

**What is the difference between admissible and consistent heuristic?**

A heuristic is admissible if it never overestimates the true cost to a nearest goal. A heuristic is consistent if, when going from neighboring nodes a to b, the heuristic difference/step cost never overestimates the actual step cost.

## Is 0 A consistent heuristic?

“For any search space, there is always an admissable and consistent A* heuristic”. Well, i know that there is always an admissable heuristic, for example zero, since its an underestimation of the real cost (althoug this would lead to uniform cost instead of a*).

**Is 0 a consistent heuristic?**

### What is difference between admissible and consistent heuristic?

**How do you determine if a heuristic is admissible and consistent?**

#### Can a heuristic be zero?

**IS A * heuristic?**

A heuristic, or a heuristic technique, is any approach to problem-solving that uses a practical method or various shortcuts in order to produce solutions that may not be optimal but are sufficient given a limited timeframe or deadline.

## When is a heuristic considered to be admissible?

Admissible Heuristic: A heuristic is admissible if the estimated cost is never more than the actual cost from the current node to the goal node. To understand this, we can imagine a diagram as depicted below.

**When is the heuristic C ( N, N ) consistent?**

A heuristic is consistent if the cost from the current node to a successor node, plus the estimated cost from the successor node to the goal is less than or equal to the estimated cost from the current node to the goal In an equation, it would look like this: C (n, n’) + h (n’) ≤ h (n)

### When is a heuristic consistent with an estimated cost?

A heuristic is consistent if the cost from the current node to a successor node, plus the estimated cost from the successor node to the goal is less than or equal to the estimated cost from the current node to the goal A heuristic is admissible if the estimated cost is never more than the actual cost from the current node to the goal node.

**Are there any consistent heuristics in the search space?**

However, it is no longer consistent – there isn’t a clear relationship between the heuristic estimates at each node. for any three nodes a, b and c in the search space, with the understanding that the cost is computed using the actual cost between adjacent nodes and using the heuristic otherwise.