Local search is a particular way of solving a CSP. It keeps improving the values until all the constraints are satisfied. It iteratively keeps updating the variables until we arrive at the destination. These algorithms modify the value during each step of the process that gets us closer to the goal. In the solution space, the updated value is closer to the goal than the previous value. Hence it is known as a local search.

Local search algorithm is a heuristic search algorithm. These algorithms use a function that calculates the quality of each update. For example, it can count the number of constraints that are being violated by the current update or it can see how the update affects the distance to the goal. This is referred to as the cost of the assignment. The overall goal of local search is to find the minimal cost update at each step.

Hill climbing is a popular local search technique. It uses a heuristic function that measures the difference between the current...