Dynamic Programming

Dynamic programming problems require making a sequence of interrelated decisions, where each decision corresponds to one stage of the problem.

• True

• False

Dynamic programming problems always have a finite number of states

• True

• False

The states in a dynamic program are the various possible conditions in which the system might be at that stage of the problem

• True

• False

The effect of the policy decision is to transform the current state to a state associated with the beginning of the next stage

• True

• False

Dynamic programming, as linear programming, can solve only deterministic problems

• True

• False

In a network representation, the state variables are shown in:

• the links

• the nodes

• the values on the links

The principle of optimality in Dynamic programming means:

• knowledge of past states is necessary for determining the optimal policy

• knowledge of the current state is sufficient for determining the optimal policy

• the optimal policy is independent of the states of the system

The markovian property for Dynamic programming means:

• the past is important to determine the future

• the past is irrelevant to determine the future

• the past is somewhat relevant to determine the future

Select all the elements of a dynamic program

• Stage variable

• Backwards recursion

• Policy variables

• Performance function