# Ai Ai (and MoGaL)

Stephen Tavener, with Cameron Browne · Java · `checked` ·
**licence and cost `unverified`**

## What it optimises for

General game playing **with analysis aimed at game authors**. Ai Ai is
built on **MoGaL** (Modular Game Library), a general game system by
Browne and Tavener assembled from Java blocks glued by a JSON-like
language. `checked`

## How a game is defined

Hand-coded in Java for efficiency, **or** assembled from blocks using a
JSON-based scripting language. `checked`

## What it can analyse

**This is the important part and the reason this profile exists.** Ai Ai
"has quite a lot of analysis functions and contains analysis tools for
game authoring", and plays via MCTS variants. `checked`

The metric family in this research tradition — Browne, and work building
on it — includes **turn metrics: branching factor, drama, killer moves,
lead changes**; and **endgame metrics: completion, duration, advantage**.
`checked` (from the literature; that Ai Ai computes this exact set is
`unverified`).

**Lead change is treated as close to drama**: a game that never changes
leader is tedious, and one that changes too often is chaotic. `checked`

## What it does not do

- No federated authority: no concept of the game's owner ruling on an
  undecided case. `unverified`
- No provenance binding to a publisher's dataset. `unverified`
- Its measurements are outputs, not claims under adversarial review.

## Relevance to clay-borg

**Track C, and it substantially reframes it.** `Positioning.md` §4
described "assimilated knowledge about why games work" as open ground.
**It is not.** Ai Ai computes designer-facing measures of exactly this
kind and has done for years.

Also **Track A**: MoGaL's "Java blocks glued by JSON" is a third point on
the description-language axis, between Ludii's ludemes and hand-written
code — and closer to what a clay-borg game definition might look like.

## What to steal

- **The metric family itself.** Drama, lead change, completion, duration
  and branching factor are directly computable from our journals, and we
  already compute cruder cousins (win rate, arm rate, action counts).
- **The framing that a metric is for the author**, not for an agent.

## What to avoid

Adopting the metrics without their assumptions. *Drama* and *lead change*
are defined against a notion of "who is ahead", which in a co-operative
game with a defection mechanic is not obvious — GROUND's SHARED GROUND
mode has no individual leader at all, and `Modes.csv` says its tiebreak
is "Not applicable". **A metric imported without checking that its
subject exists here is the wrong-subject error**
([`../specs/Taxonomy.md`](../specs/Taxonomy.md) §2.2).

## Open questions

- The exact metric list Ai Ai produces, and their definitions.
- Whether any of them are defined for co-operative or hidden-role games.
- Licence, and whether the analysis is usable headlessly.

## Sources

- Ai Ai home (http://mrraow.com/index.php/aiai-home/aiai/) — **certificate
  expired, not fetched**; description above is from search results and the
  mirror at https://aiai.website/
- *Efficient Reasoning in Regular Boardgames*
  (https://arxiv.org/pdf/2006.08295) — for the MoGaL/Ai Ai relationship
- *Evolutionary Tabletop Game Design: A Case Study in the Risk Game*
  (https://arxiv.org/pdf/2310.20008) — for the turn/endgame metric families