# Question: Sometimes MDPs are formulated with a reward function R s a

Sometimes MDPs are formulated with a reward function R(s, a) that depends on the action taken or a reward function R (s, a, s’) that also depends on the outcome state.

a. Write the Bellman equations for these formulations.

b. Show how an MDP with reward function R (s. a. s’) can be transformed into a different MDP with reward function R(s, a), such that optimal policies in the new MDP correspond exactly to optimal policies in the original MDP.

c. Now do the same to convert MDPs with R (s, a) into MDPs with R (s).

a. Write the Bellman equations for these formulations.

b. Show how an MDP with reward function R (s. a. s’) can be transformed into a different MDP with reward function R(s, a), such that optimal policies in the new MDP correspond exactly to optimal policies in the original MDP.

c. Now do the same to convert MDPs with R (s, a) into MDPs with R (s).

## Answer to relevant Questions

Consider the 4 x 3 world shown in Figure.a. implement an environment simulator for this environment, such that the specific geography of the environment is easily altered. Some code for doing this is already in the online ...Prior to 1999, teams in the National Hockey League received 2 points for a win, 1 for a tie, and 0 for a loss. Is this a constant-sum game? In 1999, the rules were amended so that a team receives 1 point for a loss in ...A good straw man” learning algorithm is as follows: create a table Out of all the training examples identify which output occurs most often among the training examples; call it d. Then when given an input that is not in ...For each of the following determinations write down the logical representation and explain why the determination is true (if it is):a. Zip code determines the state (U.S.).b. Design and denomination determine the mass of a ...Explain how to apply the boosting method naive Bayes learning. Test the performance of the resulting algorithm on the restaurant learning problem.Post your question