Non-Programming Alternative - MDP - Policy Evaluation Algorithm - Q Learning - IT Assessment Answer

Assessment Task:

Non-Programming Alternative IT Assessment Answer

Task Description:

Question 1

Assume a known MDP as above: In all states except B & E, your agent can perform 4 actions: Up, Down, Left, Right. In squares B & E your agent can only take the Exit action and an immediate reward of +10 & -10 respectively. You agent’s actions are successful 90% of the time; 10% of the time the agent moves in one of the two orthogonal (perpendicular) directions, with equal probability. If the movement is blocked by a wall (the blue squares, or the perimeter of the grid), the agent stays in place. For example, if your agent is in square C, and picks the Right action, 90% of the time it stays in place, 5% of the time in A, and 5% of the time in E.

Given the policy, p, as specified by the arrows, evaluate it for three iterations using the Policy Evaluation algorithm - fill in the values in the table below:

Question 2

 Consider the same Gridworld as in question 1, but now assume that the MDP is unknown, i.e. you do not know the Reward Function, R, nor do you know the Transition Function, T. Your agent interacts with the Gridworld environment for four episodes as below.

(a) Using Model-based Reinforcement Learning, estimate the values below:
T(A, Up, C)=
T(A, Up, A)=
T(C, Left, A)=
T(C, Up, E)=
----
R(E, Exit, T) =
R(A, Up, C) =
R(B, Exit, T)=
R(C, Up, E)=

(b)  After all Reward & Transition functions are learned as per (a), what methods could you use to solve the MDP?

(c) Using Q-Learning (Model-free), and assuming that all Q-Values for every pair have been initialized to 0, and a learning rate of (a = 0.6), fill in the Q-Table below after your agent has experienced the first three episodes above. The red cells show that the pair is not available. You can ignore these. Note that you will have to create the intermediate tables (after Episodes 1 and 2) for yourselves to get to the last one (after Episode 3), but only this last one is required here.

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