74、I guess there are still some things we both have to learn together.

202、Algorithms designed using dynamic programming are similar to those developed using divide-and-conquer in that both solve a problem by breaking it down into several subproblems that can be solved recursively.The difference between the two is that in the dynamic programming approach, the results obtained from solving smaller subproblems are reused in the calculation of larger subproblems.Thus, dynamic programming is a bottom-up technique that usually begins by solving the smallest subproblems, saving these results, and then reusing them to solve larger and larger subproblems until the solution to the original problem is obtained.This is in contrast to the divide-and-conquer approach, which solves problems in a top-down fashion.In this case the original problem is solved by breaking it down into increasingly smaller subproblems, and no attempt is made to reuse previous results in the solution of any of the subproblems.It is important to realize that a dynamic programming approach is only justified if there is some degree of overlap in the subproblems.The underlying idea is to avoid calculating the same result twice.This is usually accomplished by constructing a table in memory, and filing it with known results as they are calculated.These results are they used to solve larger subproblems.Dynamic programming is often used to solve optimization problems.In an optimization problem, there are typically a large number of possible solutions, and each has a cost associated with it.The goal is to find a solution that has the smallest cost -- this is referred to as an optimal solution.(3)、In order to solve the problem, what will a dynamic programming approach do?

202、Algorithms designed using dynamic programming are similar to those developed using divide-and-conquer in that both solve a problem by breaking it down into several subproblems that can be solved recursively.The difference between the two is that in the dynamic programming approach, the results obtained from solving smaller subproblems are reused in the calculation of larger subproblems.Thus, dynamic programming is a bottom-up technique that usually begins by solving the smallest subproblems, saving these results, and then reusing them to solve larger and larger subproblems until the solution to the original problem is obtained.This is in contrast to the divide-and-conquer approach, which solves problems in a top-down fashion.In this case the original problem is solved by breaking it down into increasingly smaller subproblems, and no attempt is made to reuse previous results in the solution of any of the subproblems.It is important to realize that a dynamic programming approach is only justified if there is some degree of overlap in the subproblems.The underlying idea is to avoid calculating the same result twice.This is usually accomplished by constructing a table in memory, and filing it with known results as they are calculated.These results are they used to solve larger subproblems.Dynamic programming is often used to solve optimization problems.In an optimization problem, there are typically a large number of possible solutions, and each has a cost associated with it.The goal is to find a solution that has the smallest cost -- this is referred to as an optimal solution.(2)、 The feature of dynamic algorithm is?

202、Algorithms designed using dynamic programming are similar to those developed using divide-and-conquer in that both solve a problem by breaking it down into several subproblems that can be solved recursively.The difference between the two is that in the dynamic programming approach, the results obtained from solving smaller subproblems are reused in the calculation of larger subproblems.Thus, dynamic programming is a bottom-up technique that usually begins by solving the smallest subproblems, saving these results, and then reusing them to solve larger and larger subproblems until the solution to the original problem is obtained.This is in contrast to the divide-and-conquer approach, which solves problems in a top-down fashion.In this case the original problem is solved by breaking it down into increasingly smaller subproblems, and no attempt is made to reuse previous results in the solution of any of the subproblems.It is important to realize that a dynamic programming approach is only justified if there is some degree of overlap in the subproblems.The underlying idea is to avoid calculating the same result twice.This is usually accomplished by constructing a table in memory, and filing it with known results as they are calculated.These results are they used to solve larger subproblems.Dynamic programming is often used to solve optimization problems.In an optimization problem, there are typically a large number of possible solutions, and each has a cost associated with it.The goal is to find a solution that has the smallest cost -- this is referred to as an optimal solution.(1)、When you meet a problem with some degree of overlap in the subproblems, which algorithm may work best?

201、The MAC address associated with a station is fixed at the time of its .

200、With a business that requires multiple hubs, to enable all users to access the site server, the hubs must be interconnected together.

199、As computing machinery found wider and users in information management, each application tended to be implemented as a separate system with its own collection of data.

198、Flash memory blocks have to be explicitly erased they can be written to.

197、A flash file system is a file system designed for files on flash memory devices.

196、The use of folders makes it to organize files in a logical way.

195、Product engineering software is used in hardware and software products.