Backward chaining is a method of reasoning that is used in artificial intelligence and computer science to solve problems by starting with the goal and working backwards to determine the necessary steps to achieve it. It is often used in rule-based systems, where the goal is to find a set of rules that can be applied to a given problem to arrive at a solution.

In backward chaining, the system starts by identifying the goal or desired outcome and then works backwards to determine the necessary conditions that must be met in order to achieve that goal. It checks the current state of the system and determines what actions or steps must be taken in order to satisfy the necessary conditions. If the necessary conditions are not met, the system continues to work backwards until it finds a set of actions or steps that can be taken to satisfy those conditions.

Backward chaining is useful for solving problems where the goal is known but the steps needed to achieve it are not, as it allows the system to determine the necessary steps by working backwards from the goal. It is often used in expert systems, where it can be used to identify the set of rules that need to be applied in order to solve a particular problem.