u/Southern-Reality762

In my math model, I decided to model risk based off the way that the risk of the actual action would change, based off a few factors like distance and the time to complete the action.

For example, in my model risk increases dramatically if you are within a certain distance from the opponent, but not by much after you enter that range. And you aren't at much risk while performing this "Action 1" if you are outside of that range. So I used a 1/log function to model it, and the risk function for Action 1 looks like 1/log of distance plus the logarithm of the time it would take to complete Action 1 (because after a certain threshold, the time it takes to compete an action doesn't increase risk much).

The reasons you would perform Action 2 are much less nuanced, so the risk function for Action 2 is just a constant based on those same factors, like 4.

And for Action 3 (doing nothing) risk is just 1 because you aren't doing anything. It's not 0 because if risk and reward were 0, the risk-reward ratio would be undefined.

The issue arose when I realized that Action 1's risk function might return 50 and Action 2's function might return 4, where both are saying "very high risk". So my first instinct is to normalize the outputs of the risk functions so I'm not comparing apples to oranges. I just have no idea how to do that, as my math model isn't using means or standard deviations the way z-scores do.

In my math model, I decided to model risk based off the way that the risk of the actual action would change, based off a few factors like distance and the time to complete the action.

For example, in my model risk increases dramatically if you are within a certain distance from the opponent, but not by much after you enter that range. And you aren't at much risk while performing this "Action 1" if you are outside of that range. So I used a 1/log function to model it, and the risk function for Action 1 looks like 1/log of distance plus the logarithm of the time it would take to complete Action 1 (because after a certain threshold, the time it takes to compete an action doesn't increase risk much).

The reasons you would perform Action 2 are much less nuanced, so the risk function for Action 2 is just a constant based on those same factors, like 4.

And for Action 3 (doing nothing) risk is just 1 because you aren't doing anything. It's not 0 because if risk and reward were 0, the risk-reward ratio would be undefined.

The issue arose when I realized that Action 1's risk function might return 50 and Action 2's function might return 4, where both are saying "very high risk". So my first instinct is to normalize the outputs of the risk functions so I'm not comparing apples to oranges. I just have no idea how to do that, as my math model isn't using means or standard deviations the way z-scores do.

I'm analyzing my first game and I wanna teach myself how to make sure there aren't flaws in my definitions or system.

Title basically. I'm taking AP Lit, BC (this is an everyday class), and these two cybersecurity courses next year but I want a half schedule for senior year. But my counselor said to take AP Lit to make it look like I'm not backing down from a challenge (I took Lang this year). If I took English at my CC and got English 12 credit that way it would report as English 12 taken at my CC to colleges. Is that perceived rigor worth the 3-2 schedule? I can't really tell.

I'm thinking Psychic Fighting because Sally uses magic (to an extent) and is scared of ghosts, and the Fighting part because of her playstyle which let's be honest involves a lot of phyiscal attacks and physical movement.

I could see Payne being a Steel Fairy type because his whole theme is that he's this godly knight. Maple is a Poison type no doubt. Maybe Poison Dark in reference to Atrocity and Seeping Chaos.

Iz is probably a Normal type and Kanade is a Fairy type or a Psychic type. Chrome is a Steel type and Drag is a Ground type for obvious reasons.

Dread is a Dark type because Normal doesn't make much sense (he's not a normal dude), his outfit kinda screams "Dark type" to me at least, and he has that pet that lets people go into shadows.

I don't feel like thinking of the other ones rn.

Working on my first big, major, multi month proof right now and I'm enjoying it. But think of the 9th graders doing half assed proofs in geometry!

So this morning I thought: why not start a club with a few other high schoolers where we lemma'd our way each week to a deep proof? I don't quite know exactly what we would prove or how deep we would go. Calculus and analysis are not needed: you can do a lot if you understand the simple concept that is a set. In fact I have not touched limits in the proof I just mentioned. I am thinking of a proof (or a mathematical model) that would mostly use geometry/sets/algebra/functions. And of course I would be there to assist if needed.

By the end of the school year my hope is that anyone who joined at the beginning would be as good at mathematical logic as I am now (in other words, able to write a not-too-hard proof if given time).

I'm posting for insights that I'm not considering right now. I hope this isn't a bad idea or that the idea of a club entitled "Proof Club" doesn't bore people or scare them away.

All I can really tell is that Maple doesn't like them because they are a counter to her massive defense? But like how and why is it a counter? Like how are piercing attacks defined?