Random search:
In this search technique, an agent just keeps checking any random state for being the goal state. This is not an effective way to search the solution because, in this search, each node can be searched again and again, there is no fixed path followed, problems like infinite searching can be faced.Breadth-first search (BFS):
In this type of search, the agent considers every state as a node of a tree data structure. It first checks the current node and then evaluates all the neighboring nodes. After all the neighboring nodes are checked, it moves towards the next set of neighboring nodes for any of the neighbor nodes, and this process continues until the search is ended. In BFS, the nodes of the tree are traversed level after level.Depth-first search (DFS):
In the DFS, the search first begins from the root node, and the first one of the child node’s sub-tree is completely traversed. First, all the one-sided nodes are checked, and then the other-sided nodes are checked.Best First Search (Heuristic Search):
In the best first search, which is also known as the heuristic search, the agent picks up the best node based upon the heuristic value irrespective of where the node is.A* search:
It is one of the best and popular techniques used in pathfinding and graph traversals. It decides the node to be traversed based on an f-score which is calculated according to some norms and the node with the highest f-score gets traversed. Here, the f-score is calculated based on misplaced events and the number of nodes that need to be moved to replace the nodes.