Dynamic programming is an optimization technique that utilizes recursion and specific rules to address, for example, NP-hard problems. The concept involves storing solutions for subproblems and reusing them when necessary, rather than recalculating their values. This approach frequently transforms the runtime complexity from exponential to polynomial, enhancing computational efficiency. Rules of dynamic programming When describing an algorithm it is defined as a dynamic algorithm if the following principles of optimization are suitable for it: =>A problem can be broken down to subproblems and is solved only once =>The solution of a subproblem might help you finding a feaseable solution for…