brycewang-stanford/awesome-journal-skills/aamas-review-process
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Checking that the SKILL.md file is still in the repository.
Use when explaining or planning around AAMAS peer review, covering OpenReview review release, the double-blind rebuttal on preliminary reviews, area-chair discussion, the mixed game-theory, MARL, and systems reviewer pool, the public posting of reviews and decisions, and how acceptance criteria weigh the interaction contribution.
Install
npx vskill@latest install brycewang-stanford/awesome-journal-skills/aamas-review-processSKILL.md
AAMAS Review Process
Use this to reason about review-stage strategy. Reopen the current CFP, OpenReview group, author and reviewer instructions, and the code of conduct before making process claims; AAMAS review specifics move between editions.
Process model
- AAMAS runs submission and review on OpenReview under the IFAAMAS namespace in recent cycles.
- Reviewers evaluate technical correctness, the significance of the interaction contribution,
the reality and rigor of the multiagent evaluation, clarity, reproducibility, and fit with agents-and-multiagent-systems scope.
- A rebuttal lets authors respond to preliminary reviews before the final decision; area chairs
then synthesize.
- Accepted papers and their reviews are published, so the review record is durable and public.
- The most useful rebuttal gives the area chair a clean rationale for acceptance, not a
point-by-point defense of every comment.
Who reviews here
- The pool mixes game theorists, multiagent-RL researchers, mechanism-design and social-choice
specialists, and systems-minded reviewers; expect at least one to read the game definition and solution concept line by line.
- Because AAMAS is specialized, a paper is likely to meet a reviewer who works on exactly its
subarea, so a vague equilibrium claim or an under-specified opponent set gets caught rather than skimmed.
- Borderline interaction papers usually fail on one of three edges: the result turns out to be
single-agent in disguise, the solution concept is never pinned down, or the multiagent evaluation is thin (self-play only, no seeds, no held-out opponents).
Scoring leverage table
| Review dimension | What raises it | What sinks it | |
|---|---|---|---|
| Correctness | A stated game, a named solution concept, and a body-level proof sketch | Hidden information structure; an equilibrium asserted but never defined | |
| Significance | A finding that only exists because agents interact | An incremental single-agent gain wearing a multiagent label | |
| Empirical support | Experiments that probe strategy: held-out opponents, deviation tests | Self-play-only curves disconnected from the claim | |
| Clarity | One notation source and a legible game description | Notation and payoff conventions that shift between sections |
Stage-by-stage realism
- Initial reviews: triage by what the area chair would weigh, not by reviewer tone.
- Rebuttal: windows are short; an early, precise reply anchored in submitted evidence beats a
late exhaustive one.
- Decision: the area chair synthesizes, and one unanswered correctness or interaction-reality
objection outweighs several resolved clarity complaints.
- Public record: assume the reviews and your rebuttal will be visible with the paper, and keep
the exchange professional and concrete.
Output format
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingAAMAS-Skills/skills/aamas-review-process/SKILL.md
Popularity
- 7-day trend score
- 5
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