Eight profiles on a common schema, each marking what was checked against a source this session and what is background recollection. Three are marked unverified in full — Machinations, the play substrates, most of RBG — and say so rather than reading as evaluations. Written straight after three review rounds whose entire yield was claims outrunning what had been checked, so the confidence rule is the first thing in the README. The survey changed the plan, which is what a survey is for. Track C was described in Positioning as open ground. It is not: Browne published 57 criteria for game quality, and Ai Ai already computes designer-facing measures — drama, lead changes, branching factor, completion, duration — from played games. The track becomes adopt, credit and find the gap. The gap looks real: those measures presume a leader, and SHARED GROUND has none — Modes.csv gives its tiebreak as "Not applicable". Track B probably adopts rather than builds. OpenSpiel implements CFR, best-response and exploitability over games that are simultaneous-move, imperfect-information and co-operative, which is all four of GROUND's awkward properties. "Does ATTACK ever pay" is a best-response question, and we spent three review rounds refining a two-policy sweep for it. The first Track B task is now one question — is exploitability meaningful for a co-operative game with a shared threshold — not a build. The cost of not surveying earlier is therefore measurable, and is recorded rather than glossed. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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Browne's game-quality criteria
Cameron Browne · not a simulator — a measurement vocabulary ·
checked that it exists and its size; the list itself unverified
What it optimises for
Answering "is this game any good" numerically, from played games, so that generated or modified games can be ranked without a human playing every one.
Browne presented 57 criteria for measuring the quality of a game.
checked
How a game is defined
Not applicable — the criteria are computed over played games, whatever produced them.
What it can analyse
The families that recur in work building on it: checked
| family | examples |
|---|---|
| turn metrics | branching factor, drama, killer moves, lead changes |
| endgame metrics | completion, duration, advantage |
Lead change is close to drama: never changing leader is tedious, too
much is chaotic. checked That framing — a good value is an interval,
not a maximum — is the transferable idea.
What it does not do
Nothing about cooperative games, hidden roles, or games with no
individual leader — at least, nothing we have confirmed. open, and it
is the question that decides how much of this is usable for GROUND.
Relevance to clay-borg
Track C is not open ground, and this is the evidence. Positioning.md
§4 proposed "assimilate knowledge about why games work" as though it were
unclaimed. There is a twenty-year literature with a canonical criterion
set, and Ai Ai computes members of it.
This is a good finding, not a bad one. It moves Track C from invent a theory of fun to adopt an existing vocabulary, credit it, and locate the gap — and the gap is plausibly real: co-operative and hidden-role games.
What to steal
- The criteria as a vocabulary for what our panels already half-measure.
- The interval framing: our register would be improved by targets that are ranges rather than "0" and "100%".
What to avoid
Importing a metric whose subject does not exist here. Lead change
presumes a leader; SHARED GROUND has none, and Modes.csv says its
tiebreak is "Not applicable". Computing lead change there would produce a
number about nothing — ../specs/Taxonomy.md §2.2.
Open questions
- The 57 criteria themselves, and which are defined for n-player co-operative play.
- Whether anyone has extended them to social-dilemma games.
- The primary source (Browne's thesis / Evolutionary Game Design) — not read, and it should be before Track C opens.
Sources
- Evolutionary Tabletop Game Design: A Case Study in the Risk Game (https://arxiv.org/pdf/2310.20008) — cites the 57 criteria and the turn/endgame metric families
- Quantifying game design (https://www.sciencedirect.com/science/article/abs/pii/S0142694X04000201)
- Measuring Board Game Distance (https://arxiv.org/pdf/2301.03913)