Summer of Math Exposition

I would like to see more code and math formulas. I would prefer if I could implement the algorithms just from the information in the video without having to look up the articles.

This is a short and interesting comparison of two algorithms to find out how to optimize farming in a video game (e.g. Silksong). I assume the two algorithms can be applied to any game, which makes this useful knowledge for any gamer. I’m not a gamer, per se, but when I do play games with random drops in different areas, I usually go to where it “feels” the most loot has been dropped. Whether that’s actually the case, I don’t know because I didn’t calculate that until now. With the knowledge imparted through this video, however, I now have a better tool than my gut feeling to find the (probably) best possible location to farm – with a little bit of extra effort, of course.

Motivation: The motivation behind this video seems clear to me. If I spend countless hours in a video game with random drops, I want to be as efficient as possible.

Clarity: The video doesn’t go too much into the details. It explains what I need to understand as a layman in a comprehensible manner. However, when I’d like to try out one of these algorithms in the future to test them for myself, I’d probably need to read the studies or watch a follow-up video, since that’s not clear yet. For instance: I have no idea how to read the formula at 2:52. After skimming the referenced papers, I find them very complicated. So this video does a good job making their contents seem less overwhelming.

Novelty: I’ve never heard about the two algorithms discussed yet. Hearing about their existence and usefulness was quite conclusive.

Memorability: The video is plain and simple. I’ll probably remember it when I’ve spent countless hours in a spot farming specific items, and I wondered whether there could have been a better spot.

A few other thoughts and considerations:

• Audio quality: You want to be heard. Having the best possible voice quality is important, because your voice is the main tool you use to convey the information.
• It would have been cool to see the algorithm(s) applied to at least one other game or situation as well, to show how generally useful they are – or an example that shows where the limits of e.g. the Track and Stop algorithm are (if there are any).
• The background music feels unintentional. It’s seemingly the same throughout the video. You can use music and SFX to emphasize specific sections of the video, to give them more weight and importance.

All in all, this is a solid, well-done video. Definitely above the average compared to the videos I’ve reviewed last year. The narration is well-done as well.

if we are looking for the ideal hunting ground, we should add (duration to get shards n reset) to this… testing each hunting ground reduces optamization due to the durration it takes to travel to each different spot, depending on how many times you intend to visit/shards you wish to get.

some pauses are too long the music gets a little abnoxious, there are times it could have been paused to focus more on your worlds.

3:22 - “in computational statistics, there are a lot of different notions of optimality” this could be elaborated on.

8:35 - lots of real good examples of real world applications

Motivation - (dont work harder, think smarter), Optamizations of things…

Novelty - putting a videogame is SoME was a based decision. however sucessive rejects isnt something new… 2013 is pretty recent. Arm fixed confidence - 2016 paper also recent for solving costly optamization problem (stating real world use).

Clarity - very clear, could have used more elaborations

Memorability - video game decision making using math

1-9 Motivation: 3 (dont work harder think smarter… Optamizations of things.) Clarity: 6 (could have used more elaborations. could have stated the exact things we were basing the optamization on in the video game) Novelty: 2 (videogame & recent articles) Memorability: 2 (video game) 13/4 = 3.25

Enjoyed the presentation & you spoke very well!

Music is too loud and the sound quality of the voiceover really fights with the bright music.

The explanations themselves were great! But the framing via Silksong might be too brief for people unfamiliar with Silksong. And I would have loved a few sentences on where the equation at 02:50 is coming from.

the connection to silksong did not seem to fit the question/ problem. the topic could have been explained without needing this specific example. if we are playing the game we are just going to go where it’s easiest to collect shards! it fell a bit short of getting to this point. i think it might have been beneficial to state the areas you were testing and some of the sampling would have been nice to see to make it clearer. there did not seem to be a definitive conclusion to the posed question about where to get optimal shards.

the music on loop was a bit too short and slighty jarring. thumbnail is great and i was hoping for more! engaging for a class, but in a more general world, the video was not as engaging as we were hoping for.