Dynamic programming in discrete time is a mathematical technique used to solve optimization problems that are characterized by a sequence of decisions made over time. In discrete time, the decisions are made at a finite number of points in time, and each decision affects the outcome of the optimization problem.
The basic idea behind dynamic programming in discrete time is to break down the problem into smaller sub-problems that can be solved sequentially. The optimal solution to the original problem can then be found by combining the solutions to the smaller sub-problems.
