This chapter is about dynamic programming, which is a more powerful approach than greedy or divide and conquer methods. The basic idea is kind of the opposite of greedy approach. You explore all possible solutions to a problem but breaking a problem up into subproblems, the building up the correct solution into larger subproblems. This may seem to be close to brute-force, but it is not because of the way it explores the possible solutions. It never explicitly looks at every solution, but carefully breaks it down so that we can find an optimal solution with a good running time.