CS 175: Project in AI (in Minecraft) Spring 2017
◦ Project Summary:
Since things may have changed since proposal (even if they haven’t), write a short
paragraph summarizing the goals of the project (updated/improved version from the proposal).
◦ Approach:
Give a detailed description of your approach, in a few paragraphs. You should summarize the
main algorithm you are using, such as by writing out the update equation (even if it is off-the-shelf). You
should also give details about the approach as it applies to your scenario. For example, if you are using
reinforcement learning for a given scenario, describe the MDP in detail, i.e. how many states/actions you
have, what does the reward function look like. A good guideline is to incorporate sufficient details so that
most of your approach is reproducible by a reader. I encourage you to use figures, as appropriate, for this,
as I provided in the writeup for the first assignment (available here:
http://sameersingh.org/courses/
aiproj/sp17/assignments.html#assignment1). I recommend at least 2-3 paragraphs.
◦ Evaluation:
An important aspect of your project, as we mentioned in the beginning, is evaluating your
project. Be clear and precise about describing the evaluation setup, for both quantitative and qualitative
results. Present the results to convince the reader that you have a working implementation. Use plots, charts,
tables, screenshots, figures, etc. as needed. I expect you will need at least a few paragraphs to describe each
type of evaluation that you perform.
◦ Remaining Goals and Challenges:
In a few paragraphs, describe your goals for the next 2-3 weeks, when
the final report is due. At the very least, describe how you consider your prototype to be limited, and what
you want to add to make it a complete contribution. Note that if you think your algorithm is quite good,
but have not performed sufficient evaluation, doing them can also be a reasonable goal. Similarly, you may
propose some baselines (such as a hand-coded policy) that you did not get a chance to implement, but
want to compare against for the final submission. Finally, given your experience so far, describe some of the
challenges you anticipate facing by the time your final report is due, how crippling you think it might be,
and what you might do to solve them.
You might need to include some math to describe what you are doing. To enable
math mode, you will need to update your
/docs/
_
layouts/default.html
by
either copying over the latest version from
https://github.com/sameersingh/
gh-skeleton/blob/master/docs/
_
layouts/default.html
, or just copy the few
lines from
https://github.com/sameersingh/gh-skeleton/commit/283c
. This
change also gives an example of how to include math in your
.md
files, i.e. by
putting L
A
T
E
X formatted equations between pairs of $$ .
3 Video Summary (30 points)
One of the submissions for the status is to create a video summarizing your progress so far. The video is limited
to
three minutes
. The video should contain a brief problem description (using images, screenshots, or screen
captures), an example capture in Malmo of how a simple baseline performs (such as at the beginning of training),
and an example capture of a run that is working. You are free to include more details, such as summary of how
you did it, some of the failure cases, or what you plan to do in the remaining weeks, but it is not needed.
You should embed the the video on the status report page on the website. For example, if you upload the
video on YouTube, add the embed video code provided by YouTube to the top of
status.md
. The video should be
of reasonably high quality, i.e. a minimum resolution of 1200
×
720 (i.e. 720p), and speech, if any, should be
comprehensible. I will create a thread on Piazza to discuss video logistics (please contribute as well as ask!).
4 Peer Grading (20 points)
In order to better familiarize yourselves with the other projects, and to train you to read and evaluate other
people’s work, we will be asking each of you to grade the progress report for
four
other projects. The peer review
assignments will be assigned individually, and thus the 20 points for completion are individual-specific, not group
specific. Your grading assignments for the projects will show up on Canvas, and has to be completed by
June 2nd,
2017
. Note that the peer grades will not be the final grade for the project, but they will definitely be taken into
account.
Project Status UC Irvine 2/ 3