# Procedure For Graph Search, reordering the open list

1. Create a search graph G consisting a start node S.

2. Create two lists open and close

3. Initially start node S is placed in open list.

4. Check whether the Sis goal node itself if it is the goal node then place S in the close list. If  S is not the goal node then generate the successors.

5. This generated successors are placed in open list.

6. If n is the goal node then simply come out. Otherwise, we expand the node n generating the set M of its   successors. So, we install them as a successors of M  in the open list.

7. So, add this  members of M to the open list. And then expand them further.

8.Now , if each member of M is already in G  then  we can decide whether or not to redirect  its pointer to n or if each member of M already on closed i.e., ,   one of the successor is already expanded then we can redirect its descendants  whatever are there to that pointer .Else we ignore  that node to be expanded further.

## How to reorder the open list

If it is uninformed search , we can reorder  according to  some orbitary  scheme ,In case of informed search it is according to some heuristic merit .Firstly we discuss about uninformed search

•  Uninformed search is also called as blind search  this is because of the fact that it do not use any information  about the likely direction of the goal nodes. We do not have any idea of the problem domain.

• So Informed search on the other hand most popularly called heuristic search are informed search technique in the sense that they use information about the domain. And to try usually ahead in the general direction of the goal.

• Informed search method and uninformed search methods are distinctly different in only either use of no information or  use of information   about the domain.

### •  Few of the uninform search methods are

• Depth-First Search
• Depth-Limited Search
• Uniform cost
• Depth-First iterative deepening
• Bidirectional Search

### Few of Informed search methods are

• Hill Climbing
• Best-First
• Greedy Search
•  Beam Search
• A and A *

### 1 Comment

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