Markov-Decision-Process: Artificial Intelligence
Objective
To expirement with some of the basic algorithms for solving MDPs on a simple domain.
Groups: You may optionally work in groups of 2 students.
Doomain: The domain is based on a simple MDP originally designed by Rich Sutton at the University of Alberta. The example describes a Markov Decision Porcess that models the life of a student and the decisions one must make to both have a good time and remain in good academic standing.
States
R = Rested
T = Tired
D = Homework Done
U = Homework Undone
8p = eight o'clock pm
Actions
P = Party
R = Rest
S = Study
any means any action has the same effect
note: not all actions are possible in all states
Red numbers are rewards
Green numbers are transition probabilities (all those not labeled are probability 1.0)
The gray rectangle denotes a terminal state.
See below for the diagram of the MDP.
