Firstly, Heuristic Search Techniques are the informed search techniques in AI. These techniques find an optimal solution for the problem. Moreover, there are four types of Heuristic Search techniques. Some of its techniques include Best First Search, A* Algorithm and AO* Algorithm.
Secondly, Blind Search Techniques are the uninformed search techniques. Moreover, there are five types of blind search. This algorithm includes breadth first search (BFS), depth first search (DFS), uniform cost search, iterative model and bidirectional search. Let us look at this algorithm in brief.
Blind Search
Breadth First Search and Depth First Search:
- Firstly, Breadth First Search uses queue whereas Depth First Search uses stack.
- Secondly, in BFS we first explore all the neighbouring nodes starting from the root node. In DFS, we go in depth of the node starting from the root node.
- Thirdly, BFS consumes more memory. And DFS consumes less memory.
- Lastly, Breadth First Search gives more accurate result than Depth First Search.
Moreover, blind search techniques does not have any domain knowledge. In this techniques, there is a domain knowledge and it is more efficient. Let us look at this technique in brief.
Heuristic Search Technique
Best First Search
Best First Search is a heuristic way to find optimal solution to a problem. Moreover, it combines Breadth First Search and Depth First Search to bring out the best outcome from both of them. Certainly, it will select the path which appears to be the best.
In addition, this algorithm uses priority queue.
Advantages of Best First Search
- Can switch between BFS and DFS
- More efficient than BFS and DFS.
Disadvantages
- Many not always give a good solution as reverse tracking is not possible.
- Moreover, it may get stuck in a loop.
A* Algorithm
A* algorithm is the simplification of Best First Search. Moreover, it expands the most promising path and avoids taking the most expensive path. It evaluates the cost on the basis of function f(n). Hence, the formula of f(n) is as follows:
f(n) = g(n) + h(n)
Here, g(n) depicts cost of initial to current state and h(n) depicts the heuristic value.
Hence, this technique will always give optimal value.
So the main difference between blind search and heuristic search is that blind search is uniformed & heuristic search is informed. Moreover, blind search does not have domain knowledge and cannot solve complex problems. Heuristic search has domain knowledge and can solve complex problems to find optimal solution.
Conclusion
In conclusion, we have learnt Heuristic Search Techniques are the informed search techniques. These techniques find an optimal solution for the problem. It includes Best First Search, A* Algorithm and AO* Algorithm..
Moreover, Blind Search Techniques are the uninformed search techniques. It includes breadth first search (BFS), depth first search (DFS), uniform cost search, iterative model and bidirectional search.
