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Aamas related work

Skill brycewang-stanford/Awesome-Journal-Skills/AAMAS-Skills/skills/aamas-related-work

Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的 Claude Code/Codex 期刊技能包,从选题、识别策略到表格规范与审稿回复全流程,助你快速发论文。

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Use when positioning an AAMAS submission against multiagent, game-theory, and reinforcement-learning literature spread across AAMAS, AAAI, IJCAI, NeurIPS, ICML, EC, and JAAMAS, including arXiv and workshop versions, concurrent submissions, prior conference versions, and the cross-community citation coverage AAMAS reviewers expect.

SKILL.md

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AAMAS Related Work

Use this to audit novelty and eligibility. Reopen the current CFP for dual-submission, anonymity, and prior-publication rules before advising authors; much of the nearest multiagent work lives at other venues, which shapes both positioning and eligibility.

Positioning checks

  • Separate the interaction novelty from engineering improvement: a new solution concept, mechanism, learning-dynamics result, coordination protocol, negotiation strategy, or empirical multiagent finding.
  • Compare across communities: AAMAS itself, the AI conferences (AAAI, IJCAI), the ML conferences (NeurIPS, ICML), and economics-and-computation venues (EC), plus the JAAMAS journal. Many landmark multiagent papers are not at AAMAS, so a bibliography that only cites AAMAS is as suspicious as one that ignores it.
  • Treat conference proceedings and journals as archival unless the current rules say otherwise.
  • Cite arXiv and workshop versions without breaking double-blind; do not point reviewers to an identity-revealing page.
  • Explain overlap with any concurrent or prior version, and do not submit duplicate archival work.

Cross-community coverage table

Literature laneTypical sourcesWhat AAMAS reviewers check
Agents / multiagent coreAAMAS, JAAMAS, IJCAI, AAAI agent tracksWhether the nearest multiagent method is compared or explicitly distinguished
Multiagent RLNeurIPS, ICML, ICLR, prior AAMASWhether MADDPG/QMIX/COMA-style cousins are cited even though they are not AAMAS papers
Game theory / mechanism designEC, GEB, algorithmic game-theory venuesWhether the solution concept and known impossibility results are acknowledged
Social choice / negotiationAAMAS, AAAI, COMSOC, ADTWhether standard axioms and strategyproofness usage are followed

A bibliography citing only deep-MARL benchmarks tells a game-theory reviewer that known equilibrium or mechanism results may be getting rediscovered - a recognizable AAMAS reject pattern no amount of benchmark strength repairs. The mirror failure - only citing classical game theory while ignoring the deep-MARL wave - loses the empirical reviewer.

Positioning vignette

Imagine the paper proposes a communication protocol that improves cooperation in a mixed-motive game. Its nearest neighbors: a NeurIPS MARL paper with emergent communication but no incentive analysis, an EC paper with a cheap-talk equilibrium but no learning, and a prior AAMAS paper on the same game with a weaker coordination result. The novelty sentence should name all three: incentives where the MARL line had none, learning where the game-theory line stayed static, and stronger coordination than the direct AAMAS predecessor.

Concurrent-work judgment calls

  • Independently concurrent arXiv work: cite neutrally, state the technical difference, and avoid priority claims reviewers cannot verify.
  • Your own workshop version: usually non-archival and citable, but verify against the current CFP and phrase the citation so double-blind survives.
  • When unsure about a venue's archival status, declare the overlap in the submission form rather than gambling on a chair's reading.

Output format

[Eligibility] clear / needs declaration / risky
[Closest literatures] <agents / MARL / game-theory / social-choice>
[Nearest 3 works] <work -> distinction>
[Archival-overlap risk] <none / issues>
[Novelty sentence] <AAMAS-ready interaction contrast>

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.