Question

In Artificial intelligence:

3.3. What are the problems of global searches? Explain.

Answer 1

Global Search: A global search algorithm works by looking for an optimal solution in the complete graph. This can be differentiated from a local search which just looks for an optimal solution in a small part of the graph. For example the Dijkstra's Algorithm is a global search while the Beam Search is a local search algorithm.

Problems of Global Searches:

Here are some problems associated with global searches:

• Slow: A global search is much slower than a local search as it has to look for the optimal solution in the complete graph of choices. Further it has to take action based on a huge lot of choices at all steps. This makes the algorithm slow.
• Huge Memory Requirement: A global search has to keep in its frontier all the nodes that are candidates to an optimal solution. Since it has to look at the complete graph for the optimal solution, the frontier becomes a large set. This set has to be stored in memory (RAM) and requires a lot of memory for storage.
• Repeated States in Search: If the search is such that the states may be repeated, the algorithm may get stuck and may not be able to complete the entire graph.

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