
Aamas Review Process
Use when explaining or planning around AAMAS peer review, covering OpenReview review...
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-review-process -g -a claude-code -y- Repository
- brycewang-stanford/Awesome-Journal-Skills1.3k
- Category
- Engineering
- Updated
- 1mo ago
- License
- MIT
- Context cost
- Lightabout 798 tokens
- Runs scripts
- No, instructions only
What it does
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.
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).
