Part 1. That is a good analitical approach to split into groups and then synthesize the build. But let me give an example of how one unexpected/unconventional synergy looks.
Perk 1: You see blood drops on the ground better.
Perk 2: You get a notification whenever a bird is disturbed by an enemy, and you can pinpoint the direction.
Both these perks would fall into general and quite a big bin of “information perks”. Both their descriptions do not give any hint that they would work together.
Here is the scenario which happened a lot in my games:
You damage one opponent and leave immediately without tracking him down. The opponents will communicate between themselves that you changed your plans, and they will react accordingly by changing positions. Their relocation likely disturbes a bird and you can quickly find and damage the second opponent. The first would likely find a hiding spot to heal, but you switch targets again and track the first guy by his blood drops. But switching targets again encouraged opponents to take strategically better spots and disturb birds, giving you information again.
That creates a loop, where you flip flop between reacting to the info those 2 perks give, AND creates a bit of confusion and inefficiency in the opponent team AND they waste time (which is a limited resource) by responding to your changes of targets.
(If you were hunting just the first player, like if you had no info perks and were afraid to lose track of the injured guy, all 3 other players would sit on their tasks and feel safe).
Many perks in the game are not like “get +x% to y stat”. They introduce a new mechanic. If all perks woul give some numerical benefit to the stats, I think it would be possible to use Wolfram language to solve a system of 100+ equations.
Part 2.
Thanks for the video right on topic. I did not know the problem is called Full factorial analysis.
The video shows a problem with 3 slots and 2 possible values for each slot. Those values can repeat (LHH).
In my problem there are 4 slots, and 116 possible unique categorical values, which cannot repeat from slot to slot. I do not understand the principles of scaling here. Soo, I build a table, such than any column contains equal observations while having and not having a perk. I don’t quite understand how the table is generated, but thanks for the food for thought, I’ll dig in this direction.
http://neilsloane.com/doc/cent4.html According to this page, all tables have unsuitable “orientation”.
For example, there is a table with 99 factors and 2 levels, but the task would need 4 factors and 116 levels. The amount of levels must be much bigger.
Part 1. That is a good analitical approach to split into groups and then synthesize the build. But let me give an example of how one unexpected/unconventional synergy looks.
Perk 1: You see blood drops on the ground better. Perk 2: You get a notification whenever a bird is disturbed by an enemy, and you can pinpoint the direction.
Both these perks would fall into general and quite a big bin of “information perks”. Both their descriptions do not give any hint that they would work together. Here is the scenario which happened a lot in my games: You damage one opponent and leave immediately without tracking him down. The opponents will communicate between themselves that you changed your plans, and they will react accordingly by changing positions. Their relocation likely disturbes a bird and you can quickly find and damage the second opponent. The first would likely find a hiding spot to heal, but you switch targets again and track the first guy by his blood drops. But switching targets again encouraged opponents to take strategically better spots and disturb birds, giving you information again. That creates a loop, where you flip flop between reacting to the info those 2 perks give, AND creates a bit of confusion and inefficiency in the opponent team AND they waste time (which is a limited resource) by responding to your changes of targets. (If you were hunting just the first player, like if you had no info perks and were afraid to lose track of the injured guy, all 3 other players would sit on their tasks and feel safe).
Many perks in the game are not like “get +x% to y stat”. They introduce a new mechanic. If all perks woul give some numerical benefit to the stats, I think it would be possible to use Wolfram language to solve a system of 100+ equations.
Part 2. Thanks for the video right on topic. I did not know the problem is called Full factorial analysis.
The video shows a problem with 3 slots and 2 possible values for each slot. Those values can repeat (LHH). In my problem there are 4 slots, and 116 possible unique categorical values, which cannot repeat from slot to slot. I do not understand the principles of scaling here. Soo, I build a table, such than any column contains equal observations while having and not having a perk. I don’t quite understand how the table is generated, but thanks for the food for thought, I’ll dig in this direction.
http://neilsloane.com/doc/cent4.html According to this page, all tables have unsuitable “orientation”. For example, there is a table with 99 factors and 2 levels, but the task would need 4 factors and 116 levels. The amount of levels must be much bigger.