Algorithm AO * for reducing problems with AND OR GRAPH

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Algorithm AO *

A * can be computer algorithms used in traversing drivers and graphs. It is used in the method of tracing an efficient guided path between several points called nodes.

In the AN * algorithmic rule, you traverse the tree in depth, keep moving forward and add the overall value to reach the target position from the current situation and add it to the value to reach the current position.

Algorithm AO *

In AO * algorithms, you follow the same method, although there are obstacles to cross specific approaches.

Once you have traversed these paths, the value of all paths from the previous node is added to this level where you search for the targeted position, despite the fact, Move.

REDUCTION OF THE PROBLEM:

Until now, we have been thinking about how to search the graph, through which we want to find a way to achieve a goal. This type of structure represents the real fact that we all know a way to move from the anode to the target position if we are told in a situation where the nodes with the stress of the branches will be explained.

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AND – OR Chart

AND – or graphic.

AND – OR graphic

AO * ALGORITHM:

Let G be the graph only with the introduction of the INIT node.

Repeat the follow up until you insert INIT in Solvi or H (INIT)> property.

A) Select the node suddenly from the path leading to INIT (it's called NODE)

B) Generate the successor of NODE. If none, set NODE = futility (that is, NODE fails); Otherwise, each SUCCESSOR that is not for the ancestors of NODE, does the following:

I add SUCCESSSOR to G

ii. If SUCCESSOR can be a terminal node, solve it and set HK (SUCCESSOR) = NULL.

iii. If SUCCESSPR is not a terminal node, calculate it.

C) Promote the newly discovered graph information by searching for the following: S should have a set of salt-like nodes or nodes whose H-values have been changed and their parents should return the values … S Repeat the trace until you reach the point. S is empty:

I remove the knot from the sand that lights it.

ii. Calculate the value of each bow that comes out. Assign the minimum value of your successor to HK

iii. Mark this route by marking the minimum arch value at step ii-iv. All nodes linked to the new labeled arc are fixed, then mark it as current.

v. If the label is solved or if its value has just been changed, broadcast your new value through the chart. So add all the ancestors from S. to S.

AND – OR graphic

AND – OR graphic

AND – OR graphic

In the form (A), the upper node A has been expanded to produce 2 zones that move to B and move to C-D. The numbers on each node represent the value of F on it (the value of reaching the target position from the current position). For the sake of simplicity, it is thought that each operation (ie the implementation of a rule) corresponds to the cost, that is to say that at each successor, the value of each component of each component. With the information available to date, it seems that C is the most promising node extended since F = 3, but going through B is preferable to using C, we use D and the value nine. Get also (3 + 4 + 1 + 1). He will be 6 (5 + 1) through B

To develop it, the selection of the next node does not depend only on a value, although the node is only the initial mode of the best current path. Figure (B) shows it well. The node of the form seems to be the most promising node with at least the F value. But to use the GG does not match the current beat path, the AO algorithm for problem reduction should always use GH with the value nine, it is then demanding that the arc be used (with the value 27). The route from A to B, E-F is the best with the full value (17 + one = 18). In this method, we will see that the following 3 things must be completed to see the AN & G graph.

Cross the graph starting from the initial node and follow the best current path, then submit all the nodes present on the path and not yet extended.

Select one of these amazing nodes and expand it. Add them to your successor graph and PCF (the cost of the remaining distance).

Modify the 'F estimate' of the new expanded node to reflect the new information provided by your successor. Boost this revision back across the chart. Check the current best path.

The estimate of the modified value is not required in the tree * A * algorithm. This can be {car} because extended nodes are tested again in the AO * algorithm so that the best current path can be selected. The work of AO * Formula is shown in the image as follows:

With reference to the figures, the initial node is expanded and D is initially marked due to the node. D Another E-F production order has been developed. AO Problem Reduction Algorithm: The value of the FD has been updated to ten. Going back, we will see that the Arch B-C finish is the best. It is currently marked because of the current best route. B and C should be reported. This method continues until all the methods have no answer or cause deadlocks, it shows that there is no answer. The AA algorithm is always the lowest cost from one node to the other and it is independent of the path across the opposite nodes.

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The algorithm to perform another horizontal search of the graph is given below. Unlike the A * algorithm that opens and closes 2 lists, the AO algorithm uses the same structure. The GG represents part of the search graph generated from this point. Each node reaches its immediate successor and its immediate predecessors, the problem reduction algorithm, in addition to the path cost value during all nodes of the response. The price to get the current node "live" from the starting node is not preserved in the formula A *.

Since it is out of the question to calculate this value, it may be possible for several methods to be used in the same state. The algorithm AO * predicts the quality of the node. Apart from this, the value called useless should be used. If the calculation of the answer exceeds the allowed cost, the inventions are too large to be applied