--- name: AAMAS Review Process slug: aamas-review-process category: Quality description: Strategic guidance for the AAMAS peer review process, covering rebuttal tactics, scoring dimensions, and reviewer expectations for multi-agent and game theory papers. github: "https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AAMAS-Skills/skills/aamas-review-process" language: Stata stars: 880 forks: 106 install: "git clone https://github.com/brycewang-stanford/Awesome-Journal-Skills" added: 2026-07-20T06:49:39.818Z last_synced: 2026-07-29T06:37:40.675Z canonical_url: "https://dirskills.com/skills/aamas-review-process" --- # AAMAS Review Process Strategic guidance for the AAMAS peer review process, covering rebuttal tactics, scoring dimensions, and reviewer expectations for multi-agent and game theory papers. **Install:** `git clone https://github.com/brycewang-stanford/Awesome-Journal-Skills` ## README # 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 ```text [Current stage] submitted / reviews / rebuttal / decision / camera-ready [Decision actors] [Likely leverage] [Forbidden moves] [Next response move] ```