# Tag Info

Accepted

### What are the differences between Q-Learning and A*?

Q-learning and A* can both be viewed as search algorithms, but, apart from that, they are not very similar. Q-learning is a reinforcement learning algorithm, i.e. an algorithm that attempts to find a ...
• 37.1k
Accepted

### Why is A* optimal if the heuristic function is admissible?

This is well covered in the corresponding chapter of Russell & Norvig (chapter 3.5, pages 93 to 99 (Third Edition)). Check that out for more details. First, let's review the definitions: Your ...
• 9,037
Accepted

### How is iterative deepening A* better than A*?

A* is a best-first search algorithm, which means that it is an algorithm that uses both "past knowledge", gathered while exploring the search space, denoted by $g(n)$, and an admissible heuristic ...
• 37.1k
Accepted

### What are the differences between A* and greedy best-first search?

Both algorithms fall into the category of "best-first search" algorithms, which are algorithms that can use both the knowledge acquired so far while exploring the search space, denoted by $g(n)$, and ...
• 37.1k
Accepted

• 901
1 vote
Accepted

### How can the A* algorithm be optimized?

Check below reference url for A* algorithms ... https://takinginitiative.wordpress.com/2011/05/02/optimizing-the-a-algorithm/ https://en.wikipedia.org/wiki/Heap_%28data_structure%29
1 vote

### How can the A* algorithm be optimized?

The first step of optimisation is to measure where inside the implementation most time is spent -- you don't actually optimise the algorithm itself, but a specific implementation of it. This step ...
• 5,252
1 vote

### What kind of search method is A*?

A* is an informed search algorithm. A* informed because it is based on the use of a heuristic function, which estimates the distance of each node to the goal, that is, the heuristic function provides ...
• 37.1k
1 vote

### What are the differences between A* and greedy best-first search?

What you said isn't totally wrong, but the A* algorithm becomes optimal and complete if the heuristic function h is admissible, which means that this function never overestimates the cost of reaching ...
• 11
1 vote
Accepted

### How does A* search work given there are multiple goal states?

Question 1: First of all, you state that that the goal G2 will be found first by relying on the expansion order R, B, D, G2. This is wrong. It is extremely easy to ...
• 200

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