What Is Bidirectional Search?

Bidirectional search is the perfect example of the phrase "two heads are better than one." This type of search and sort activity combines two directional approaches so that your generator can search in two directions simultaneously. That way, you decrease the amount of search activity needed to achieve a particular result. It's like combining two different methods for achieving a goal, like using a compass and a map or following a paper trail and tracking from footprints in mud to ensure you don't miss anything. Bidirectional search is not a brute-force search algorithm. It's a form of directed search that relies on a heuristic to determine the best way to proceed. The heuristic is an educated guess about the best next step to move toward your goal state. It's educated because it comes from all kinds of data about how systems behave and how you've been able to solve similar problems in the past. Bidirectional search is not just going from top to bottom or vice versa. It's going through every possible path between your starting point and your goal state at least once before making assumptions about which is most likely to succeed in completing your goal. Bidirectional search is like backpropagation but for search. If you need clarification on what that means, don't worry! It's pretty straightforward. Backpropagation is a method of machine learning where artificial neural networks are built with the ability to feed outputs back into previous neural layers. In this way, the network learns from its mistakes and can change its behavior based on those lessons. It's a way of teaching algorithms to think more like humans and to learn from their own mistakes. Bidirectional search is also a way of teaching algorithms how to think more as humans do. Still, in this case, it's about teaching them to think about their previous actions and make decisions based on them (rather than just relying on their past experiences).