Artificial Intelligence Search Algorithms

Introduction to search algorithms

Search algorithms are the set of problem solving operations which are applied to track down the particular information from the collection of data. Different techniques are used to locate the data with the help of search algorithms. For instance, in linear search data is searched sequentially. Search starts from the first element and approaches to the desired element in a sequence. Whereas, in binary search array sorting is done first and then comparison starts from middle and proceed towards the selected information.

Search Algorithms in Artificial Intelligence

In artificial Intelligence, search algorithms are subjected in such way that operation of locating an element takes place with best possible combination. It is more understandable with the help of example. While playing chess game we have multiple options to move a substance but acquiring the best option is the way of working of search algorithms in artificial intelligence.

Search Algorithms in Artificial Intelligence

Classification of AI search algorithms

Al search algorithms are further categorized in following types. First of all we will discuss the Brute-Force search strategies which include state description, set of valid operators, Initial state and goal state description.

1-Breadth-First search algorithms are the most common and simplest type of search algorithms in which search starts from the first node (source node) and move towards the next node through the layers and ultimately approaches to the root node by the exploration of the neighbor nodes.

Breadth-First search algorithms

2- Depth-First search algorithms are implemented for self-repeating (recursive) data structures. It is similar to breadth first search the only difference is the order of execution. This search algorithm moves on a pattern of backtracking. Backtracking means if the agent doesn’t find node in the path, it backtrack to the previous node until unless find a new node. It is based on the concept of LIFO which stands for “Last in first out”.

Depth-First search algorithms

3-Bidirectional search algorithms have two direction paths of searching that’s why this search chooses the shortest path. Search starts from initial state and the goal state and meet in the middle.

4-Uniform cost search algorithms methodology is based on solving the general graphs with the help of optimal cost. At each step, every node expands depending on the order of their cost from the root.

Uniform cost search algorithms

5-Iterative deepening depth-first search algorithms are same as the depth first search. In this search specifically depth first search is executed again and again increasing the depth limits until unless goal is found.

Iterative deepening depth-first search algorithms

Now we will discuss the heuristic search strategies,

6-Greedy best first search algorithms are pure heuristic algorithms. The terminology lies on principle of expanding the node closest to goal. The execution of this search depends on the most promising node of graph.

Greedy best first search algorithms

7-A* search algorithms are also the informed search algorithms in which all the paths are taken into the account to find out the shortest path to the solution ( goal). This is also one of the simple types of informed searching algorithms.

The other search algorithms also include local search algorithms which are following

8- Hill Climbing Search is an arbitrary way of finding solution by incremental change in solution. This search initially finds an arbitrary solution and the incremental changes are applied till approaches to goal.

Advantages of Artificial Intelligence Search Algorithms

Instead of using the simple searching techniques, artificial intelligence search algorithms are more prominent and preferable because they have very fast execution. Multiple ways of search are available according to the situation. The advantage of maximum accuracy in result is also remarkable.

Disadvantages of Artificial Intelligence Search Algorithm

There are also some disadvantages of AI search algorithms. While searching each layer of node consumes maximum memory comparatively. Sometimes the search is subjected to the unknown path where algorithm failed to terminate and kept on moving infinitely. While using a priority queue in greedy best first search there is tendency that it may stick in between the loops. More numbers of paths can also make a complication in execution.

Conclusion

It is the invention of modern-age and leading technology. It can be very helpful in particular sections but it also have some complexities which need more exploration and invention to overcome these drawbacks and make an artificial intelligence really smart, reliable and obviously intelligent.

Tags: Artificial Intelligence, Artificial Intelligence Tutorial, Search Algorithms