mathlab , Computer Engineering

Assignment Help:
Windy Grid World

This assignment is to use Reinforcement Learning to solve the following "Windy Grid World" problem illustrated in the above picture. Each cell in the image is a state. There are four actions: move up, down, left, and right. This is a deterministic domain -- each action deterministically moves the agent one cell in the direction indicated. If the agent is on the boundary of the world and executes an action that would move it "off" of the world, it remains on the grid in the same cell from which it executed the action.
Notice that there are arrows drawn in some states in the diagram. These are the "windy" states. In these states, the agent experiences an extra "push" upward. For example, if the agent is in a windy state and executes an action to the left or right, the result of the action is to move left or right (respectively) but also to move one cell upward. As a result, the agent moves diagonally upward to the left or right.
This is an episodic task where each episode lasts no more than 30 time steps. At the beginning of each episode, the agent is placed in the "Start" state. Reward in this domain is zero everywhere except when the agent is in the goal state (labeled "goal" in the diagram). The agent receives a reward of positive ten when it executes any action {\it from} the goal state. The episode ends after 30 time steps or when the agent takes any action after having landed in the goal state.
You should solve the problem using Q-learning. Use e-greedy exploration with epsilon=0.1 (the agent takes a random action 10 percent of the time in order to explore.) Use a learning rate of 0.1 and a discount rate of 0.9.
The programming should be done in MATLAB. Students may get access to MATLAB here. Alternatively, students may code in Python (using Numpy). If the student would rather code in a different language, please see Dr Platt or the TA.
Students should submit their homework via email to the TA ([email protected]) in the form of a ZIP file that includes the following:
1. A PDF of a plot of gridworld that illustrates the policy and a path found by Q-learning after it has approximately converged. The policy plot should identify the action taken by the policy in each state. The path should begin in the start state and follow the policy to the goal state.
2. A PDF of a plot of reward per episode. It should look like the diagram in Figure 6.13 in SB.
3. A text file showing output from a sample run of your code.
4. A directory containing all source code for your project.
5. A short readme file enumerating the important files in your submission.
Updates
You can initialize the Q function randomly or you can initialize it to a uniform value of 10. That is, you can initialize Q such that each value in the table is equal to 10.
There have been questions about how to know when the algorithm has converged. The algorithm has converged when the value function has stopped changing signficantly and the policy has stopped changing completely. Since we are using q-learning, the algorithm should converge to a single optimal policy.
Please also submit a short readme file with your homework that enumerates the important files in your submission.


Related Discussions:- mathlab

Ida* search - artificial intelligence, IDA* Search - artificial intelligenc...

IDA* Search - artificial intelligence: A* search is a sophisticated and successful search strategy. In fact, a problem with A* search is that it must keep all states in its me

Define class p, Define class P  The class of all sets L that can be kno...

Define class P  The class of all sets L that can be known in polynomial time by deterministic TM. The class of all decision problems that can be decided in polynomial time.

Difference between synchronous and asynchronous updates, What is the differ...

What is the difference between Synchronous and Asynchronous updates? A program asks the system to perform a particular task, and then either waits or doesn't wait for the task

Ethernet 10 base 2 is an example of which topology, Ethernet 10 Base 2 is a...

Ethernet 10 Base 2 is an example of               network topology. (A)  Bus                                           (B)  Ring (C)  Star

What is the basic approach of page replacement, What is the basic approach ...

What is the basic approach of page replacement?  If no frame is free is available, find one that is not currently being used and free it. A frame can be freed by writing its co

Salient points about addressing mode, Salient points about addressing mode ...

Salient points about addressing mode are:  This addressing mode is employed to initialise value of a variable. Benefit of this mode is that no extra memory accesses are

What is drop-down list, A dialog box such as a File menu that have one comm...

A dialog box such as a File menu that have one command until it is clicked when a number of dissimilar commands "drop-down."

Operating sustem, describe the action by thread library to context switch ...

describe the action by thread library to context switch between user level threads

Vector-scalar instructions- vector processing, Vector-Scalar Instructions :...

Vector-Scalar Instructions : In this type, when the combination of vector and scalar are fetched and saved in vector register. These instructions are denoted with the many function

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd