D&D.Sci Scenario Index
There have been a lot of D&D.Sci scenarios, but there’s a lot of variance between them in complexity and quality. Some are more difficult, and might not be a good place to start, while others are much simpler—some were very good, while others on reflection didn’t flow quite right.
Unfortunately, LW karma doesn’t track the quality of these scenarios very well: often mediocre scenarios are higher-karma than better scenarios (whether because they had good writing around a poor scenario, or because people upvoted before playing them, or just because more people happened to be online and see them).
If you’re interested in playing D&D.Sci scenarios, but don’t know where to start, this index (compiled by frequent authors abstractapplic and aphyer, we’ll try to keep this updated going forwards) is a good reference point to make sure you can pick good scenarios at a difficulty level you’re comfortable with.
If you’re new to D&D.Sci, you should probably start with the lower-Complexity scenarios and move up to the higher-Complexity ones. Scenarios with Quality Rating 1-2 are probably less worth playing, while the higher-rated ones are ones we’d recommend.
If you disagree with any of these ratings let us know, we’re happy to review—there were some scenarios where we disagreed on the correct rating while compiling this list, and we’d appreciate your comments as an outside view, especially if you’re a frequent player!
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Keen-eyed readers will notice a correlation between this column and the ‘Complexity’ column.
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abstractapplic: These scenarios were attempts to convey / demonstrate specific ideas with real-world relevance; I judge that they failed at this; I therefore grade them a little less generously than you might.
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abstractapplic: These scenarios were attempts to convey / demonstrate specific ideas with real-world relevance; I judge that they succeeded at this; I therefore grade them a little more generously than you might.
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aphyer: I thought this scenario was great, and still do, but given that absolutely nobody but me liked it I am forced to admit that the odds suggest you will not like it either.
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aphyer: I’m quite proud of the writing in this scenario, but the actual scenario itself was mediocre.
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aphyer: Sadly the difficulty rating for this scenario arises less from complexity and more from tedium: the scenario doesn’t have an intricate model with sneaky multivariate effects, it just has way too many simple effects to juggle and dull bits of work to do.
- D&D.Sci Dungeonbuilding: the Dungeon Tournament by (14 Dec 2024 4:30 UTC; 50 points)
- D&D.Sci Tax Day: Adventurers and Assessments by (15 Apr 2025 23:43 UTC; 47 points)
- D&D Sci Coliseum: Arena of Data by (18 Oct 2024 22:02 UTC; 42 points)
- D&D.Sci Thanksgiving: the Festival Feast by (22 Nov 2025 2:26 UTC; 40 points)
- 's comment on D&D.Sci: Whom Shall You Call? [Evaluation and Ruleset] by (27 Sep 2024 17:16 UTC; 3 points)
- 's comment on Cheaters Gonna Cheat Cheat Cheat Cheat Cheat by (9 May 2025 15:16 UTC; 3 points)
I’m a big fan of this series. I think that puzzles and exercises are undersupplied on LessWrong, especially ones that are fun, a bit collaborative and a bit competitive. I’ve recently been trying my hand at some of the backlog, and it’s been pretty cool. I can feel that I’m getting at least a bit better at compressing the dimensionality of the data as I investigate it.
In general, I’d guess that data science is a pretty important epistemological skill. I think LessWrongers aren’t as strong in it as they ideally would be. This is in part because of a justified suspicion that people just pour in data and confusion, and get out more official-looking confusion. I’d say that a central point of this series is: how do you avoid confusing yourself with data by actually thinking about things?