Basically, starts searches forward from an initial state and backward from goal state. As till both meets to identify a common state. Moreover, initial state path is concatenated with the goal state inverse path. Each search is done only up to half of the total path.
The bidirectional search algorithm is a search algorithm used in the field of artificial intelligence and computer science to find the shortest path between two nodes in a graph. Unlike traditional search algorithms that start from the initial state and explore until they find the goal state (unidirectional search), bidirectional search explores from both the initial state and the goal state simultaneously. This approach can be more efficient, especially in situations where the search space is large or when the graph is structured in such a way that the distance between the initial and goal states is roughly equal in both directions.
The basic idea of the bidirectional search algorithm is to perform two simultaneous searches, one starting from the initial state and the other starting from the goal state, until the two searches meet in the middle. This is achieved by maintaining two sets of explored states, one for each direction, and alternating between expanding nodes in each direction.
The advantage of bidirectional search is that it can potentially reduce the time and space complexity of the search process compared to traditional unidirectional search algorithms, particularly in scenarios where the branching factor of the graph is high or the search space is vast.
In summary, the bidirectional search algorithm is a strategy for finding the shortest path between two points in a graph by simultaneously exploring from both the initial and goal states towards each other, aiming to meet in the middle. This approach can offer efficiency gains in certain scenarios compared to traditional unidirectional search algorithms.