Program the MDP supported robot of Section 13.3.3 in the language of your choice. Experiment with different values of a and b that can optimize the reward. There are several interesting possible policies: If recharge is a policy of A(high), would your robot learn that this policy is suboptimal? Under what circumstances would the robot always search for empty cans, i.e., the policy for A(low) = recharge is suboptimal?

Data from 13.3.3