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Dec 9, 2021 at 12:21 answer added Personman timeline score: 0
Oct 1, 2021 at 20:10 comment added Nosajimiki This reminds me of a learning AI that learned to play Tetris. The developers gave it access to all of the same controls a human player would have, and let if find the best solution. The AI quickly learned when it became unable to score more points that it could pause the game thus preventing it from ever losing. This particular Optimal Losing Strategy is called a Rage Quit and is the optimal solution for not loosing in most games.
Sep 23, 2021 at 19:21 answer added ryanyuyu timeline score: 1
Sep 23, 2021 at 19:06 comment added neph I think you might get some traction asking a similar question over on the math stack exchange. At its heart, I think this is an applied game theory question
Sep 23, 2021 at 8:38 comment added nick012000 Well, there'd definitely be optimal losing strategies for a misere game where you win if you lose.
Sep 22, 2021 at 18:27 comment added L. Scott Johnson Many algorithms prefer moves that win more quickly or that lose more slowly. Delaying the inevitable loss is certainly how computers play chess once the outcome (with perfect play) is known (likewise choosing mate-in-3 over mate-in-5 moves). But those are just artificial/spurious goals placed into the game by the programmers. They don't reflect the reality of the game: a win in any number of moves is equally good as any other win. Likewise a loss is a loss no matter how delayed.
Sep 22, 2021 at 11:45 answer added m90 timeline score: 5
Sep 22, 2021 at 7:21 answer added murgatroid99 timeline score: 3
Sep 22, 2021 at 6:30 history edited murgatroid99 CC BY-SA 4.0
Use a better tag, remove the now out-of-date message about the tags
S Sep 21, 2021 at 21:41 review First questions
Sep 22, 2021 at 3:01
S Sep 21, 2021 at 21:41 history asked Pineapple Fish CC BY-SA 4.0