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Aamas Related Work

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brycewang-stanford
aamas-related-work

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.

Overview

Publisherbrycewang-stanford
RepositoryAwesome-Journal-Skills
Skill nameaamas-related-work
Stars
1.2K
Forks
159
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by brycewang-stanford on GitHub. Read the source before you install it.

Installation

Install the Aamas Related Work AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AAMAS-Skills/skills/aamas-related-work
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git /tmp/Awesome-Journal-Skills
mkdir -p .claude/skills
cp -r /tmp/Awesome-Journal-Skills/AAMAS-Skills/skills/aamas-related-work .claude/skills/aamas-related-work
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aamas Related Work in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aamas Related Work on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aamas Related Work is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

text
[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>

Frequently asked questions

What does the Aamas Related Work AI skill do?

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.

Why use Aamas Related Work on TypingMind?

Because you install it once and use it with any model. Aamas Related Work is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aamas Related Work in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AAMAS-Skills/skills/aamas-related-work. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Aamas Related Work?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aamas Related Work?

As many as you like. As long as a model supports skills, you can use Aamas Related Work with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aamas Related Work AI skill free?

Yes. It is published on GitHub by brycewang-stanford under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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