#1 Recursive Algorithm It refers to a way to solve problems by repeatedly breaking down the problem into sub-problems of the same kind. The classic example of using a recursive algorithm to solve problems is the Tower of Hanoi. #2 Divide and Conquer Algorithm Traditionally, the divide and conquer algorithm consists of two parts: 1. breaking down a problem into some smaller independent sub-problems of the same type; 2. finding the final solution of the original issues after solving these more minor problems separately. The key points of the divide and conquer algorithm are: If you can find the repeated sub-problems and the loop substructure of the original problem, you may quickly turn the original problem into a small, simple issue. Try to break down the whole solution into various steps (different steps need different solutions) to make the process easier. Are sub-problems easy to solve? If not, the original problem may cost lots of time. #3 Dynamic Programming Algorithm Developed by Richard Bellman in the 1950s, the dynamic programming algorithm is generally used for optimization problems. In this type of algorithm, past results are collected for future use. Like the divide and conquer algorithm, a dynamic programming algorithm simplifies a complex problem by breaking it down into some simple sub-problems. However, the most significant difference between them is that the latter requires overlapping sub-problems, while the former doesn’t need to. #4 Greedy Algorithm This is another way of solving optimization problems – greedy algorithm. It refers to always finding the best solution in every step instead of considering the overall optimality. That is to say, what he has done is just at a local optimum. Due to the limitations of the greedy algorithm, it has to be noted that the key to choosing a greedy algorithm is whether to consider any consequences in the future. #5 Brute Force Algorithm The brute force algorithm is a simple and straightforward solution to the problem, generally based on the description of the problem and the definition of the concept involved. You can also use "just do it!" to describe the strategy of brute force. In short, a brute force algorithm is considered as one of the simplest algorithms, which iterates all possibilities and ends up with a satisfactory solution. #6 Backtracking Algorithm Based on a depth-first recursive search, the backtracking algorithm focusing on finding the solution to the problem during the enumeration-like searching process. When it cannot satisfy the condition, it will return "backtracking" and tries another path. It is suitable for solving large and complicated problems, which gains the reputation of the "general solution method". One of the most famous backtracking algorithm example it the eight queens puzzle.
