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Discussion: What do you all predict will be the most common tactics? #26
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Same, I also think that many submissions will be variants on tit-for-tat. It will be interesting to see how the tournament turns out! |
No way a random is gonna win. If there’s several tit-for-tatters out there, they’ll all defect half the time with the randos, drastically reducing the rando’s score. |
Grim Trigger, being the best strategy, I think will be the most iterated upon, but maybe not the most common. So yea, probably tft. |
What makes you think it's the best strategy? |
it consistently gets first place. that's why. |
tisfortat actually consistently gets first place. Doesn't grim trigger lose too many points against randoms and detective strategies? |
Grimtrigger beats random, but it loses points from titfortat. |
Every test I run, grim tripper always gets first, not sure how its different for you. |
Good lord, what other strategies did you put in that put grimTrigger in first?!? |
So it was called "beNice" and on the first turn it defects, then checks what the opponent did on that turn, if they were nice (cooperated), I would cooperate the whole time, if they were mean (defected) I would be mean for every remaining turn. I completely forgot about it and it just really changed the leaderboard. |
As I outlined in my comment on #27, I think the optimal solution here is a "forgiving" tit-for-tat (not That last piece- the forgiveness mechanic- is the unsolved component of this problem. I expect people who will submit things to do so with the intention of winning, so I suspect the meta will be dominated by tit-for-tat variants and specifically tit-for-tat variants with forgiveness rules. This will lead to boring 3/3 matches in most cases but the forgiving tit-for-tats will compete against one another based on how well they handle the strategies that defect unprovoked but have some deterministic component that can be used to largely maintain a C/C loop and/or recover some of the loss by getting a D/C +5 right after the surprise C/D (so
Someone should really submit |
Oh good god, a couple anti-detectives that are out there just out of spite for the tit-for-tats could really break this game lol |
I might be wrong about the non-viability of unprovoked defections. It's basically a wash between I wrote a simple ultimateDetective that does this and it fares pretty well in my tit-for-tat-heavy meta. I'm sure it can be optimized further but perhaps detectives/unprovoked defections aren't the dead end I think they are. If you're able to sufficiently exploit "clever" strategies and trick them into cooperating while you periodically defect, you can get a huge advantage. |
I did submit |
Hahaha well if you submitted In light of that, I think the optimal strategy is a:
Although I'm having trouble thinking of abusive counterplay against, e.g., a deferred tit-for-tat. Anything that can possibly tolerate a tat without responding with a tit is exploitable (e.g., |
So I just rewrote |
@hand-burger You can use the head-to-head file in #31 to figure out why (by looking at which strategies |
I'm not exactly sure what you mean, so I made a public repo with edit: Never mind I got it, anyways there's still a repo with |
My strategy is called grandpa_checking_you-_play. It always tells the truth, and adds "are you winning, kid?" on memory. At the end, if it loses it returns a smile. I believe this will be the way to go. |
Very good strategy! I think it will win every time |
I think some people will troll and do a tactic which detects TFT and then always defects, or random which will detect if you defect it too much and then will grudge. |
I'm using a machine learning based strategy, and I'm not expecting it to win at all, since a well-crafted detective will almost always be better at dealing with the more common strategies. My strategy wins almost every round, but in the process loses too many points, and can't get a top spot at all. Currently I downloaded I4vr0v's fork and I'm training it on some of them, such as all the detective and tit for tat variants, conMan, etc. But mine is just a gimmick, and wasn't expected to win in the first place. After all, I'm participating in a carykh coding challenge. I think my decision to make something machine-learn-y kinda proves that I'm a fan. (btw I'm not good at coding at all, in any way, so that's probably another reason my strategy is so bad.) |
How did you manage to save your model? I am building a machine-learning strategy as well, but I'm struggling with keeping all the data in one python file |
I took advantage of "memory" ad stored the model there. I made the model a single object using a class, and I just said return {the choice} [{The model}, {other information}]. After that, earlier in the script, i detect if the variable "memory" is a list or not, and if it is, the model = memory[0], and if it isn't, I generate a new one. Of course this isn't the only way to do this, there probably exists a better way to do it. |
I personally predict lots of submissions will be variants on tit-for-tat.
Commenters in youtube speculate lots of people will submit the random one-liner.
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